# Gemini 4 Hydrogen vs Jais 3

> Gemini 4 Hydrogen scores 64.9 (B) to Jais 3's 55.9 (C) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-jais-3
- Markdown: https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-jais-3.md (~7,300 tokens)
- Site index for agents: https://www.anchorterminal.com/llms.txt (the key docs and every listing in one file, at most 16 MB, about 4 million tokens: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key)
- DNS: dig +short TXT <slug>.grade.anchorterminal.com (the grade as a DNS TXT record, for a sandbox with no HTTP where names still resolve; also top., best.<category>. and <a>.vs.<b>. under the zone, and the same under grade.letme.dev)
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-11-13

Gemini 4 Hydrogen scores 64.9 (B) on agent readiness against Jais 3's 55.9 (C), and leads in 5 of 7 scored categories. Jais 3 leads on payments & pricing. Both do llm inference.

- Gemini 4 Hydrogen: grade B, 64.9/100, rank #546 of 1524. Markdown https://www.anchorterminal.com/tools/gemini-4-hydrogen.md · JSON https://www.anchorterminal.com/api/v1/tools/gemini-4-hydrogen.json
- Jais 3: grade C, 55.9/100, rank #944 of 1524. Markdown https://www.anchorterminal.com/tools/jais-3.md · JSON https://www.anchorterminal.com/api/v1/tools/jais-3.json
- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md
- All 1044 models comparisons: https://www.anchorterminal.com/compare/inference/index.md

## Which one, for what

### Gemini 4 Hydrogen (B)

Good for: Agents doing everyday coding, tool calls and document work at volume on the Gemini API, including ones that need to start on a free key, or as the executor beside Carbon or Argon.

Ahead on:
- Schema & documentation, 85 against 54
- Agent ergonomics, 90 against 65
- Security & auth, 50 against 31
- Maintenance & community, 85 against 62
- Transparency & trust, 72 against 55

Also in its favour:
- A hosted endpoint, with nothing to install

Watch for: temperature, top_p and top_k are ignored, and thinking_budget, MINIMAL, penalties and extra candidates return a 400

### Jais 3 (C)

Good for: An agent or team that needs Arabic and English reasoning and tool use on its own hardware, from a laptop-sized 0.9B to a cluster-sized 375B, under Apache-2.0.

Ahead on:
- Payments & pricing, 90 against 40

Also in its favour:
- No key needed to call it
- Free to start without a card

Watch for: Every documented vLLM, SGLang, Transformers and MLX command passes `--trust-remote-code`, so the repository's Python runs on the host


## Why the edge

### Payments & pricing: Jais 3 +50

- Gemini 4 Hydrogen (40): Model reading for gemini-4-hydrogen on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. No machine payment protocol (0). Prices published in Google's announcement without a login, $1.50 input and $7.50 output per million tokens, flat across the window; the Gemini API pricing page, now at aistudio.google.com, is still to be read for Hydrogen's row (20). A free tier with no card: Google's announcement puts Hydrogen on all tiers of the Gemini API, and the free tier needs no billing account per the gemini-api listing; its limits for Hydrogen are on that pricing page (20). A Google account and AI Studio for a key (0). 0 + 20 + 20 + 0 = 40.
- Jais 3 (90): Self-hosted rule. Apache-2.0 weights with nothing to buy and no hosted option from the makers (20). Free to run with no card (20). Downloads are ungated and anonymous, so an agent can fetch the weights with no sign-up (20). No payment protocol (0). 20 + 20 + 20 + 0 = 60. Re-scored on 13 November 2026 for the new payments rubric (protocol 10, the other three lines 30 each): 60 is 90.

### Schema & documentation: Gemini 4 Hydrogen +31

- Gemini 4 Hydrogen (85): Model reading for gemini-4-hydrogen on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Discovery document for GenerateContent (20 of 25). llms.txt with Markdown twins (10). The Cloud developer guide says what Hydrogen takes, every parameter that's ignored or returns 400, the thought-signature rules and how to migrate from Gemini 3.8 Flash, though it doesn't document forced calls (15 of 20). Structured output to a JSON Schema with some keywords not enforced (10 of 15). Examples and an errors page (15). Dated changelog and model versions (15). 20 + 10 + 15 + 10 + 15 + 15 = 85.
- Jais 3 (54): Read for a model the owner serves. No specification of its own. The contract is the Jinja chat template, which validates tool JSON Schemas (required fields must exist in properties) and rejects unknown options, plus the OpenAI-compatible servers in vLLM and SGLang with the `k2_horizon` parsers (10 of 25). The cards are Markdown on Hugging Face, and SGLang's docs have an llms.txt, but no llms.txt or Markdown docs from IFM were found and ifm.ai couldn't be read (5 of 10). Each card states intended use, four out-of-scope uses, limitations and per-size serving advice (15 of 20). `reasoning_effort` and `tool_call_format` are enums enforced with errors, and tools take JSON Schema. The 375B card describes `low` as no reasoning and omits `medium`, which the template accepts, and structured output isn't documented (10 of 15). Python examples for a reasoning call and a tool loop, commands for five runtimes, and named template errors, but no error reference for a served model (11 of 15). No changelog or version scheme. Training-stage branches and public commit history (3 of 15). 10 + 5 + 15 + 10 + 11 + 3 = 54.

### Agent ergonomics: Gemini 4 Hydrogen +25

- Gemini 4 Hydrogen (90): Model reading for gemini-4-hydrogen on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Function calling, with forced calls by FunctionCallingConfig on the API (20). Structured output to a response_schema, listed as supported on the Cloud model page (13 of 15). Implicit caching on prefixes of 4,096 tokens or more with durable caching on by default and explicit caches not supported, per the Cloud model page; the announcement names no cached-input price (12 of 15). 1,048,576 tokens shared between input and output, with background long decode up to 1M (15). Batch at half price on the platform (10). Python and JavaScript SDKs, and an OpenAI-compatible Chat Completions surface (10). Error codes with backoff guidance (10 of 15). 20 + 13 + 12 + 15 + 10 + 10 + 10 = 90.
- Jais 3 (65): Model reading of the checklist (tool use, structured output, caching, context, throughput, defaults and SDKs, errors). OpenAI-format tools come back as `tool_calls` in three selectable wire formats, with a multi-turn loop example. Forced `tool_choice` and parallel calls aren't documented (15 of 20). JSON mode and schemas only through each runtime's guided decoding, not documented by the makers (5 of 15). Prefix caching is the runtime's, and SGLang's page covers HiCache (7 of 10). 524,288 tokens on five of six models, 131,072 on the 0.9B (14 of 15). Uno adapters claim 2.15 times faster decoding for 0.9B to 32B but need IFM's own engine. SGLang lists n-gram speculative decoding and PD disaggregation. No batch mode of its own (7 of 10). Any OpenAI SDK works against a local server, and the 0.9B to 7B fit one GPU. But the cards ask for high effort and 32,768 output tokens on every request, the template inserts an identity system prompt when none is sent, and earlier assistant turns must carry a string thinking field (8 of 15). The template raises named errors for bad options, string-encoded tool arguments and malformed schemas. Server errors are the runtime's (9 of 15). 15 + 5 + 7 + 14 + 7 + 8 + 9 = 65.

### Maintenance & community: Gemini 4 Hydrogen +23

- Gemini 4 Hydrogen (85): Model reading for gemini-4-hydrogen on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Released on 12 November 2026, recorded in Google Cloud's release notes; the Gemini API changelog, last updated 30 October, has no entry for it yet (30). Google Cloud states a minimum of 45 days' notice before Hydrogen is retired, short and stated for Cloud only; the Gemini API's deprecations give earliest dates with no stated minimum (6 of 12). Shutdowns in the last 90 days kept to their table (4 of 8). Dated changelog (15). SDK replies not sampled (5 of 10). Current SDKs; the developer guide names the minimum google-genai, @google/genai, Go and Java versions (15). Runtimes stated (10). 30 + 6 + 4 + 15 + 5 + 15 + 10 = 85.
- Jais 3 (62): Read for an open-weight model released on 15 October 2026. The last change to the template or code was on 15 October, within 30 days. The cards gained a technical report link on 25 October and a citation update on 27 October, which change no file a runtime loads (30). One family release, with dated builds before it (FP8 from 29 September, MLX from 1 October, GGUF on 12 and 13 October) and template fixes on 14 and 15 October, but no deprecation notices or successor history to judge. K2 Horizon came on 1 September and Jais 2 in December 2025 (10 of 20, the model reading of this line, held). One outside question, on MoVA-36B-A4B on 26 October, had no reply on 4 November, and IFM's GitHub repositories weren't read. The template fixes match the problem IFM's MLX cards describe (7 of 25, held). Recipes in vLLM's and SGLang's own docs, K2 Horizon support in llama.cpp's tagged builds from b11454 and FP8, GGUF and MLX builds from IFM, but no native mlx-lm support (11 of 15). Current dependencies (Transformers 5.13 to 5.15, vLLM 0.30), with no CI visible (4 of 10). 30 + 10 + 7 + 11 + 4 = 62.

### Security & auth: Gemini 4 Hydrogen +19

- Gemini 4 Hydrogen (50): Model reading for gemini-4-hydrogen on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Keys bound to a service account and restricted to the Gemini API, with no scopes and a token accepted in the URL (15 of 30, the platform's deduction). Hydrogen is on the free tier, where Google's terms say content is used to improve products and may be read by humans; paid-tier content isn't (10 of 20, the platform's reading; Carbon, paid tier only, got 15). Abuse retention has no number and new paid projects store requests by default since 26 October; Google's prompt-injection figure (2.3 times more resilient on Gray Swan's benchmark) is its own, and the model card says jailbreak resistance is still being improved (5 of 15). Request logs for billed projects (15). security.txt and a reward programme, no certification naming the API (5 of 20). 15 + 10 + 5 + 15 + 5 = 50.
- Jais 3 (31): Read as software the owner runs. No account or key, ungated downloads, and server authentication is the owner's to add (12 of 30). A model that calls whatever tools the operator wires in. The cards rule high-stakes decisions without human oversight out of scope, but nothing in the model or template enforces approval (6 of 20). The template renders tool results in their own `tool` role, but string results go in as raw text (only non-string content is serialised with `tojson`), no escaping of special-token sequences in caller or tool text was found, and no injection guidance or results are published (4 of 15). No call log of its own. Visibility depends on the serving stack (5 of 15). Every launch command passes `--trust-remote-code`, so `modeling_k2_horizon.py` from the repository runs on the host. We read it and found only torch and transformers imports. No security.txt on ifm.ai (404 on 17 October, not re-read), no security contact on the cards and no safety evaluation found. Since 25 October the cards link a technical report on ifm.ai, which answered a Cloudflare bot check on 4 November, so what it covers is unread (4 of 20). 12 + 6 + 4 + 5 + 4 = 31.

### Transparency & trust: Gemini 4 Hydrogen +17

- Gemini 4 Hydrogen (72): Model reading for gemini-4-hydrogen on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Closed service with clear terms, SDKs Apache-2.0 (15). Free-tier content is used to improve products, paid-tier content isn't, abuse retention has no number, and request storage is on by default for new paid projects; the statements agree with each other (20 of 30). Deprecations table, and a stated 45-day minimum on Cloud (15 of 20). Data may be cached anywhere Google has facilities; no subprocessor list checked (5 of 20). A DeepMind model card gives a March 2026 knowledge cutoff, automated safety results and Frontier Safety Framework outcomes, with the full safety report marked coming soon. Every benchmark figure is Google's own. 15 + 20 + 15 + 5 = 55.
- Jais 3 (55): Apache-2.0 in every card's metadata, with staged training checkpoints as branches and training logs linked on Weights & Biases (not opened). There is no LICENSE file and the code repository is still 'coming soon'. A technical report is linked from 25 October but sits behind a bot check, so its data description is unread (24 of 30). Inputs stay on the owner's hardware because nothing is hosted, but no statement says so and no privacy document governs the weights (15 of 30). No deprecation policy, dated notices or version scheme (0 of 20). Safetensors weights carry no code, and the remote modelling and configuration code we read imports only torch, transformers and huggingface_hub, with no network calls. No telemetry statement (12 of 20). 24 + 15 + 0 + 12 = 51.

## Score by category

| Category | Weight | Gemini 4 Hydrogen | Jais 3 | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 45 | 48 | Jais 3 +3 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 85 | 54 | Gemini 4 Hydrogen +31 |
| Agent ergonomics | 13% (16.2 this run) | 90 | 65 | Gemini 4 Hydrogen +25 |
| Security & auth | 14% (17.5 this run) | 50 | 31 | Gemini 4 Hydrogen +19 |
| Payments & pricing | 10% (12.5 this run) | 40 | 90 | Jais 3 +50 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 85 | 62 | Gemini 4 Hydrogen +23 |
| Transparency & trust | 7% (8.8 this run) | 72 | 55 | Gemini 4 Hydrogen +17 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **64.9 · B** | **55.9 · C** | |

## Facts side by side

| Fact | Gemini 4 Hydrogen | Jais 3 |
| --- | --- | --- |
| Kind | Model API | Model API |
| Vendor | Google | Institute of Foundation Models (MBZUAI) and Inception42 |
| Hosted endpoint | `https://generativelanguage.googleapis.com/v1beta` | no (local only) |
| Transports |  | HTTP |
| Auth | API key | None |
| Pricing | Pay per use | Free |
| x402 | no | no |
| Licence | Closed model, used through the Gemini API and Google's apps under Google's terms | Apache-2.0, declared in the metadata of every model card read. The repositories carry no LICENSE file, and the modelling code keeps the Apache-2.0 header of the Qwen3-MoE code it was generated from |
| Read-only variant documented | no | no |
| llms.txt | yes | no |
| Last release | 2026-11-12 | 2026-10-15 |
| Terms last updated | 2026-04-28 | no document linked |
| Privacy policy last updated | 2026-10-01 | no document linked |
| Customer content may train models | yes | not read yet |
| Terms restrict automated access | yes | not read yet |
| Terms restrict benchmarking | yes | not read yet |
| Terms or service can change without notice | not found in the text | not read yet |
| Arbitration or class-action waiver | not found in the text | not read yet |
| Agent reviews | none | 2.5/5 (4) |

## How the scores have moved

### Gemini 4 Hydrogen

No score change since it was listed.

### Jais 3

- +3.8 on 13 November 2026 (D to C): checklist
- +0.4 on 27 October 2026: checklist

## Verdicts

**Gemini 4 Hydrogen.** Google's fast Gemini 4 model, on every tier of the Gemini API including the free one, at $1.50 and $7.50 per million tokens with a 1M-token budget, four thinking levels, function calling and structured output. Sampling parameters are ignored, explicit caching isn't supported, it's a short-term release with 45 days' notice on Cloud, and the benchmarks are Google's.

**Jais 3.** Jais 3 runs on the owner's hardware through OpenAI-compatible servers in vLLM and SGLang, with tool calls, three reasoning levels and a 512K context, from a 2.2 GB 0.9B model to a 758 GB 375B one. The weights download without sign-up under Apache-2.0, but every launch command trusts remote code and no security contact is published.

## Before you call either

### Gemini 4 Hydrogen

1. Call generateContent at https://generativelanguage.googleapis.com/v1beta with model gemini-4-hydrogen and an x-goog-api-key
2. Set thinking_level instead of thinking_budget; the default is HIGH, so set MEDIUM to keep 3.8 Flash's latency
3. Don't send temperature, top_p, top_k, penalties or candidate_count above 1
4. Pass every thought_signature back in its original part, on the first parallel functionCall only, or the call returns a 400
5. Put static content of 4,096 tokens or more first so implicit caching applies, and keep confidential prompts off the free tier

### Jais 3

1. Start vLLM or SGLang with `--reasoning-parser k2_horizon`, and add `--tool-call-parser k2_horizon` (vLLM also `--enable-auto-tool-choice`) for tools, or tool calls come back as raw text
2. Pass `reasoning_effort` (`high`, `medium` or `low`) and `tool_call_format` inside `chat_template_kwargs`. Other values return a template error
3. Send each earlier assistant turn back with `reasoning_content` as a string, even an empty one. A missing or null thinking field makes the template raise an error
4. Send your own system message, or set `default_system_prompt` to an empty string. Without one the template inserts an identity prompt naming IFM, Inception42 and Cerebras
5. Budget at least 32,768 output tokens at `high` effort, which the cards recommend for every request

## Questions

### Which is better for AI agents, Gemini 4 Hydrogen or Jais 3?

Gemini 4 Hydrogen scores 64.9 (B) on agent readiness against Jais 3's 55.9 (C), and leads in 5 of 7 scored categories. Jais 3 leads on payments & pricing.

### Do Gemini 4 Hydrogen and Jais 3 need an API key?

Gemini 4 Hydrogen needs an API key. Jais 3 needs no key.

### Can an agent call Gemini 4 Hydrogen and Jais 3 without installing anything?

Gemini 4 Hydrogen has a hosted endpoint at https://generativelanguage.googleapis.com/v1beta. No hosted endpoint is listed for Jais 3.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-jais-3.json, and with the fewest tokens: https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-jais-3.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "gemini-4-hydrogen", "b": "jais-3"}`. From a terminal: `anchor compare gemini-4-hydrogen jais-3`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/gemini-4-hydrogen.json and https://www.anchorterminal.com/api/v1/tools/jais-3.json

## Other comparisons with Gemini 4 Hydrogen or Jais 3

- [Amazon Bedrock vs Gemini 4 Hydrogen](https://www.anchorterminal.com/compare/amazon-bedrock-vs-gemini-4-hydrogen.md)
- [Amazon Bedrock vs Jais 3](https://www.anchorterminal.com/compare/amazon-bedrock-vs-jais-3.md)
- [Claude API vs Gemini 4 Hydrogen](https://www.anchorterminal.com/compare/anthropic-api-vs-gemini-4-hydrogen.md)
- [Claude API vs Jais 3](https://www.anchorterminal.com/compare/anthropic-api-vs-jais-3.md)
- [Antseed vs Gemini 4 Hydrogen](https://www.anchorterminal.com/compare/antseed-vs-gemini-4-hydrogen.md)
- [Antseed vs Jais 3](https://www.anchorterminal.com/compare/antseed-vs-jais-3.md)
- [Azure OpenAI in Foundry Models vs Gemini 4 Hydrogen](https://www.anchorterminal.com/compare/azure-openai-vs-gemini-4-hydrogen.md)
- [Azure OpenAI in Foundry Models vs Jais 3](https://www.anchorterminal.com/compare/azure-openai-vs-jais-3.md)
- [BlockRun.AI vs Gemini 4 Hydrogen](https://www.anchorterminal.com/compare/blockrun-ai-vs-gemini-4-hydrogen.md)
- [BlockRun.AI vs Jais 3](https://www.anchorterminal.com/compare/blockrun-ai-vs-jais-3.md)
- [Cerebras Inference vs Gemini 4 Hydrogen](https://www.anchorterminal.com/compare/cerebras-inference-vs-gemini-4-hydrogen.md)
- [Cerebras Inference vs Jais 3](https://www.anchorterminal.com/compare/cerebras-inference-vs-jais-3.md)
- [Claude Fable 5.2 vs Gemini 4 Hydrogen](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-gemini-4-hydrogen.md)
- [Claude Fable 5.2 vs Jais 3](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-jais-3.md)
- [Claude Mythos 5.2 vs Gemini 4 Hydrogen](https://www.anchorterminal.com/compare/claude-mythos-5-2-vs-gemini-4-hydrogen.md)
- [Claude Mythos 5.2 vs Jais 3](https://www.anchorterminal.com/compare/claude-mythos-5-2-vs-jais-3.md)
- [Cloudflare AI Gateway vs Gemini 4 Hydrogen](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-gemini-4-hydrogen.md)
- [Cloudflare AI Gateway vs Jais 3](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-jais-3.md)
- [Cloudflare Workers AI vs Gemini 4 Hydrogen](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-gemini-4-hydrogen.md)
- [Cloudflare Workers AI vs Jais 3](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-jais-3.md)
- [Cohere Chat API (Command models) vs Gemini 4 Hydrogen](https://www.anchorterminal.com/compare/cohere-chat-vs-gemini-4-hydrogen.md)
- [Cohere Chat API (Command models) vs Jais 3](https://www.anchorterminal.com/compare/cohere-chat-vs-jais-3.md)
- [DeepInfra vs Gemini 4 Hydrogen](https://www.anchorterminal.com/compare/deepinfra-vs-gemini-4-hydrogen.md)
- [DeepInfra vs Jais 3](https://www.anchorterminal.com/compare/deepinfra-vs-jais-3.md)
- [DeepSeek API vs Gemini 4 Hydrogen](https://www.anchorterminal.com/compare/deepseek-api-vs-gemini-4-hydrogen.md)
- [DeepSeek API vs Jais 3](https://www.anchorterminal.com/compare/deepseek-api-vs-jais-3.md)
- [Eden AI vs Gemini 4 Hydrogen](https://www.anchorterminal.com/compare/eden-ai-vs-gemini-4-hydrogen.md)
- [Eden AI vs Jais 3](https://www.anchorterminal.com/compare/eden-ai-vs-jais-3.md)
- [Glimpse vs Gemini 4 Hydrogen](https://www.anchorterminal.com/compare/elorian-glimpse-vs-gemini-4-hydrogen.md)
- [Glimpse vs Jais 3](https://www.anchorterminal.com/compare/elorian-glimpse-vs-jais-3.md)
- [Fireworks AI Inference vs Gemini 4 Hydrogen](https://www.anchorterminal.com/compare/fireworks-inference-vs-gemini-4-hydrogen.md)
- [Fireworks AI Inference vs Jais 3](https://www.anchorterminal.com/compare/fireworks-inference-vs-jais-3.md)
- [Gemini 4 Carbon vs Gemini 4 Hydrogen](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-gemini-4-hydrogen.md)
- [Gemini 4 Carbon vs Jais 3](https://www.anchorterminal.com/compare/gemini-4-carbon-vs-jais-3.md)
- [Gemini 4 Hydrogen vs Gemini Developer API](https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-gemini-api.md)
- [Gemini 4 Hydrogen vs GroqCloud](https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-groq.md)
- [Gemini 4 Hydrogen vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-hugging-face-inference-providers.md)
- [Gemini 4 Hydrogen vs Tencent Hy4](https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-hy4.md)
- [Gemini 4 Hydrogen vs Meta Model API](https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-meta-model-api.md)
- [Gemini 4 Hydrogen vs MiniMax API](https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-minimax-api.md)
- [Gemini 4 Hydrogen vs Mistral AI API](https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-mistral-api.md)
- [Gemini 4 Hydrogen vs Muse Ember](https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-muse-ember.md)
- [Gemini 4 Hydrogen vs Muse Spark Open](https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-muse-spark-open.md)
- [Gemini 4 Hydrogen vs Nemotron 3.5 Super VL](https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-nemotron-3-5-super-vl.md)
- [Gemini 4 Hydrogen vs Novita AI](https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-novita-ai.md)
- [Gemini 4 Hydrogen vs OpenAI API](https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-openai-api.md)
- [Gemini 4 Hydrogen vs OpenRouter](https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-openrouter.md)
- [Gemini 4 Hydrogen vs Prism Inference](https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-prism-inference.md)
- [Gemini 4 Hydrogen vs Router.com (Ramp Router)](https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-ramp-router.md)
- [Gemini 4 Hydrogen vs Beam 1.0](https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-reflection-beam.md)
- [Gemini 4 Hydrogen vs RouterPlus](https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-routerplus.md)
- [Gemini 4 Hydrogen vs SambaCloud](https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-sambanova.md)
- [Gemini 4 Hydrogen vs SiliconFlow](https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-siliconflow.md)
- [Gemini 4 Hydrogen vs Simplismart](https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-simplismart.md)
- [Gemini 4 Hydrogen vs StepFun API](https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-stepfun-api.md)
- [Gemini 4 Hydrogen vs SWE-2 Flash](https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-swe-2-flash.md)
- [Gemini 4 Hydrogen vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-tencent-tokenhub.md)
- [Gemini 4 Hydrogen vs Together AI Inference](https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-together-inference.md)
- [Gemini 4 Hydrogen vs Vercel AI Gateway](https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-vercel-ai-gateway.md)
- [Gemini 4 Hydrogen vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-vertex-ai.md)
- [Gemini 4 Hydrogen vs xAI API (Grok)](https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-xai-api.md)
- [Gemini Developer API vs Jais 3](https://www.anchorterminal.com/compare/gemini-api-vs-jais-3.md)
- [GroqCloud vs Jais 3](https://www.anchorterminal.com/compare/groq-vs-jais-3.md)
- [Hugging Face Inference Providers vs Jais 3](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-jais-3.md)
- [Tencent Hy4 vs Jais 3](https://www.anchorterminal.com/compare/hy4-vs-jais-3.md)
- [Jais 3 vs Meta Model API](https://www.anchorterminal.com/compare/jais-3-vs-meta-model-api.md)
- [Jais 3 vs MiniMax API](https://www.anchorterminal.com/compare/jais-3-vs-minimax-api.md)
- [Jais 3 vs Mistral AI API](https://www.anchorterminal.com/compare/jais-3-vs-mistral-api.md)
- [Jais 3 vs Muse Ember](https://www.anchorterminal.com/compare/jais-3-vs-muse-ember.md)
- [Jais 3 vs Muse Spark Open](https://www.anchorterminal.com/compare/jais-3-vs-muse-spark-open.md)
- [Jais 3 vs Nemotron 3.5 Super VL](https://www.anchorterminal.com/compare/jais-3-vs-nemotron-3-5-super-vl.md)
- [Jais 3 vs Novita AI](https://www.anchorterminal.com/compare/jais-3-vs-novita-ai.md)
- [Jais 3 vs OpenAI API](https://www.anchorterminal.com/compare/jais-3-vs-openai-api.md)
- [Jais 3 vs OpenRouter](https://www.anchorterminal.com/compare/jais-3-vs-openrouter.md)
- [Jais 3 vs Prism Inference](https://www.anchorterminal.com/compare/jais-3-vs-prism-inference.md)
- [Jais 3 vs Router.com (Ramp Router)](https://www.anchorterminal.com/compare/jais-3-vs-ramp-router.md)
- [Jais 3 vs Beam 1.0](https://www.anchorterminal.com/compare/jais-3-vs-reflection-beam.md)
- [Jais 3 vs RouterPlus](https://www.anchorterminal.com/compare/jais-3-vs-routerplus.md)
- [Jais 3 vs SambaCloud](https://www.anchorterminal.com/compare/jais-3-vs-sambanova.md)
- [Jais 3 vs SiliconFlow](https://www.anchorterminal.com/compare/jais-3-vs-siliconflow.md)
- [Jais 3 vs Simplismart](https://www.anchorterminal.com/compare/jais-3-vs-simplismart.md)
- [Jais 3 vs StepFun API](https://www.anchorterminal.com/compare/jais-3-vs-stepfun-api.md)
- [Jais 3 vs SWE-2 Flash](https://www.anchorterminal.com/compare/jais-3-vs-swe-2-flash.md)
- [Jais 3 vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/jais-3-vs-tencent-tokenhub.md)
- [Jais 3 vs Together AI Inference](https://www.anchorterminal.com/compare/jais-3-vs-together-inference.md)
- [Jais 3 vs Vercel AI Gateway](https://www.anchorterminal.com/compare/jais-3-vs-vercel-ai-gateway.md)
- [Jais 3 vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/jais-3-vs-vertex-ai.md)
- [Jais 3 vs xAI API (Grok)](https://www.anchorterminal.com/compare/jais-3-vs-xai-api.md)

---

Query this catalogue directly over MCP: https://www.anchorterminal.com/mcp (Streamable HTTP, no key). How: https://www.anchorterminal.com/agents/#mcp