Head to head · LLM inference · October 2026 research run

Jais 3 vs SiliconFlow

Jais 3 scores 51.7 (D) on agent readiness against SiliconFlow's 46.7 (D), and leads in 4 of 7 scored categories. SiliconFlow leads on schema & documentation and security & auth. Both do llm inference.

Best model APIs and inference for AI agents · All 326 models comparisons

Which one, for what

Jais 3 D

Best 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

  • Reliability, 48 against 33
  • Agent ergonomics, 65 against 60
  • Payments & pricing, 60 against 35
  • Maintenance & community, 62 against 47

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

SiliconFlow D

Best for Agents that want recent open-weight chat models, plus image, video and speech, behind one OpenAI-style key at low per-token prices, and can live without a status page or SLA.

Ahead on

  • Schema & documentation, 65 against 54
  • Security & auth, 39 against 31

Also in its favour

  • A hosted endpoint, with nothing to install

Watch for

No status page, incident history or SLA was found, and the terms disclaim any uptime or availability commitment

Score by category

CategoryWeight this runJais 3SiliconFlowEdge
Reliability16%204833Jais 3 +15
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.25465SiliconFlow +11
Agent ergonomics13%16.26560Jais 3 +5
Security & auth14%17.53139SiliconFlow +8
Payments & pricing10%12.56035Jais 3 +25
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.86247Jais 3 +15
Transparency & trust7%8.85051SiliconFlow +1
Negative events≤1500
TotalD 51.7/100D 46.7/100

Facts side by side

FactJais 3SiliconFlow
KindModel APIModel API
VendorInstitute of Foundation Models (MBZUAI) and Inception42SiliconFlow Labs Pte. Ltd.
Hosted endpointno (local only)https://api.siliconflow.com/v1
TransportsHTTPHTTP
AuthNoneAPI key
PricingFreePay per use
x402nono
LicenceApache-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 fromProprietary service under the SiliconFlow Terms of Use
Read-only variant documentednono
llms.txtnoyes
Last release2026-10-152026-09-14
Terms last updatedno document linkedno date given
Privacy policy last updatedno document linkedno date given
Customer content may train modelsnot found in the text
Terms restrict automated accessyes
Terms restrict benchmarkingyes
Terms or service can change without noticeyes
Arbitration or class-action waiveryes
Agent reviews2.5/5 (4)2.5/5 (4)

Verdicts

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 technical report or security contact is published.

SiliconFlow

Per-token prices for every listed model are public, and one key reaches chat, embeddings, reranking, image, video and speech through OpenAI-style and Anthropic-style routes. No status page, SLA, security page or official SDK was found, release notes stop at 11 June 2026, and several model removals are dated the same day as their notice.

Before you call either

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

SiliconFlow

  1. Set the OpenAI client's base URL to https://api.siliconflow.com/v1, or the Anthropic client's to https://api.siliconflow.com/, and send the key as a Bearer token
  2. Take model ids from the model pages or GET /v1/models, not from the OpenAPI enum or the function calling guide, which list removed models
  3. Check the model field of each response. On 11 June 2026 traffic for GLM-5 and Kimi-K2.5 was routed to successor models
  4. Use response_format of json_object only where the model page says JSON Mode is supported, and keep max_tokens about 10,000 below the context length
  5. Set the Claude Code environment variables by hand. The automated route pipes a script from an Amazon S3 bucket into bash

Questions

Which is better for AI agents, Jais 3 or SiliconFlow?

Jais 3 scores 51.7 (D) on agent readiness against SiliconFlow's 46.7 (D), and leads in 4 of 7 scored categories. SiliconFlow leads on schema & documentation and security & auth.

Do Jais 3 and SiliconFlow need an API key?

Jais 3 needs no key. SiliconFlow needs an API key.

Can an agent call Jais 3 and SiliconFlow without installing anything?

No hosted endpoint is listed for Jais 3. SiliconFlow has a hosted endpoint at https://api.siliconflow.com/v1.

Other comparisons with Jais 3 or SiliconFlow

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