# Fireworks AI Inference vs Vertex AI (Gemini Enterprise Agent Platform) > Vertex AI scores 88.7 (AA) to Fireworks AI Inference's 69.3 (B) for llm inference. Prices, MCP, x402, uptime and agent notes side by side. - Canonical: https://www.anchorterminal.com/compare/fireworks-inference-vs-vertex-ai - Markdown: https://www.anchorterminal.com/compare/fireworks-inference-vs-vertex-ai.md (~7,400 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 .grade.anchorterminal.com (the grade as a DNS TXT record, for a sandbox with no HTTP where names still resolve; also top., best.. and .vs.. 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: 2026-11-07 Vertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against Fireworks AI Inference's 69.3 (B), and leads in 6 of 7 scored categories. Both do llm inference. - Fireworks AI Inference: grade B, 69.3/100, rank #250 of 1486. Markdown https://www.anchorterminal.com/tools/fireworks-inference.md · JSON https://www.anchorterminal.com/api/v1/tools/fireworks-inference.json - Vertex AI (Gemini Enterprise Agent Platform): grade AA, 88.7/100, rank #2 of 1486. Markdown https://www.anchorterminal.com/tools/vertex-ai.md · JSON https://www.anchorterminal.com/api/v1/tools/vertex-ai.json - Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md - All 830 models comparisons: https://www.anchorterminal.com/compare/inference/index.md ## Which one, for what ### Fireworks AI Inference (B) Good for: Fireworks AI Inference runs open models through OpenAI-compatible chat and completion APIs. Watch for: Cloud provider outages on 11 August and 14 October hit many serverless models for hours ### Vertex AI (Gemini Enterprise Agent Platform) (AA) Good for: Google Cloud customers who need Gemini with residency, VPC-SC, provisioned throughput and an SLA, or Claude under a Google bill. Ahead on: - Reliability, 99 against 70 - Agent ergonomics, 97 against 80 - Security & auth, 97 against 77 - Maintenance & community, 91 against 65 - Transparency & trust, 90 against 69 Also in its favour: - Agent-ready, a grade of BB or better - Free to start without a card - No incidents deducted, where Fireworks AI Inference loses 3 points for them Watch for: The SLA drops from 99.5 to 95 per cent for short-term availability models, Gemini 3.7 and 3.6 Flash among them ## Why the edge ### Reliability: Vertex AI (Gemini Enterprise Agent Platform) +29 - Fireworks AI Inference (70): Public status page at status.fireworks.ai with a component per serverless model (20). The history page, read on 1 November, lists 236 incidents from 3 August to 31 October, nearly all short degradations of a single serverless model. Two hit many serverless models at once. On 11 August a cloud provider outage was 'affecting many of our serverless and dedicated deployments', with five serverless components (GPT OSS 120B, MiniMax M3 and the three Kimi K3 endpoints) in partial outage from 17:15 to 20:55 UTC and again from 01:36 to 01:49 UTC on 12 August, resolved 13 August. On 14 October a cloud provider outage set 18 serverless components to degraded performance, GPT OSS 120B, Kimi K3 and GLM 5.3 among them, from 23:06 UTC, with requests to them that 'may fail', recovery 'across the board' at 00:59 UTC on 15 October and the incident resolved at 01:53. Each is an hour or more of errors across most of the serverless catalogue, so two majors. Two majors sit between the checklist's one major (10) and several (0), so 5, as deepseek-api, black-forest-labs and telnyx-voice are read (5). The 19 October check gave the same 5 because no 90-day history could be read. A 30 October incident on deployment creation, dedicated training and batch inference was still open on 1 November. Numeric adaptive ceilings by model size, 216M total prompt, 54M uncached prompt and 2.16M generated tokens a minute for Small models (15). The rate-limits page says to honour `Retry-After` on 429 and otherwise back off with jitter, and the reliability guide covers timeouts and retries (15). Reserved throughput is 'covered by a throughput SLA' with no figure published (5 of 10). Serverless is generally available (10). 20+5+15+15+5+10 = 70. - Vertex AI (Gemini Enterprise Agent Platform) (99): Google Cloud status dashboard with per-product history (20). Its incident feed, read on 6 November, has no incident naming Vertex Gemini API, Gemini or the Agent Platform in the 90 days. The regional incidents of 20 August, 1 September and 20 October (europe-west2) and the Cloud Storage incident of 8 and 9 October didn't list it among affected products (30). Standard PayGo publishes usage tiers by 30-day spend with baseline throughput, 2,000,000 to 50,000,000 tokens a minute for Flash models and 500,000 to 10,000,000 for Pro, plus quota tables for other methods (15). A 429 page says to use the global endpoint and truncated exponential backoff, and a retry-strategy page (15). SLA of 99.5 per cent a month on generateContent and streamGenerateContent, 95 per cent for short-term availability models, and a latency SLO on Provisioned Throughput. The 429 page says pay-as-you-go 429s don't count toward the SLA error rate (10). Gemini 4 Argon reached GA on 13 October and Gemini 3.8 Flash moved to the 12-month tier, and the v1 API, 3.5 Flash-Lite and Claude Opus 5.5 are GA, but express mode was Preview at the 6 October check (9 of 10, up from 8). Up from 98 on 6 October. ### Maintenance & community: Vertex AI (Gemini Enterprise Agent Platform) +26 - Fireworks AI Inference (65): Read by the HTTP API checklist, as for cerebras-inference and together-inference. Rune 26B-A4B joined serverless on 27 October, five days before this check (30). Dated changelog entries several times a month, among them 27, 21, 19 and 18 October (20). Support replies not tested (0). Official Python SDK current, v1.2.30 tagged on 21 October after eleven tags from 1 October, no official TypeScript SDK (15). Dependency health not audited (0). The serverless overview promises 'at least 2 weeks advance notice' before a model is removed, and the 27 August removals were posted the day they took effect (see the deduction). 30+20+0+15+0 = 65. - Vertex AI (Gemini Enterprise Agent Platform) (91): Model reading. Gemini Omni 1.2 Flash GA on 5 November, Grok 4.7 GA on 27 October, Gemini 4 Argon GA on 13 October and Claude Haiku 5.5 on 7 October 2026 (30). Stable models stay at least 12 months, and since 6 October Gemini 4 Argon and Gemini 3.8 Flash are in that tier, while 3.7 and 3.6 Flash remain short-term with at least 45 days' notice once a date is set (10 of 12, up from 8). Gemini 2.5 Pro, Flash and Flash-Lite were due to retire on 20 October, three models on one date after more than 12 months, with replacements named. We didn't check partner model retirements (6 of 8, down from 8). Dated release notes on most working days, newest 5 November, and Cloud Customer Care (15). python-genai replies not sampled this run (5 of 10). Current SDKs, google-genai 3.0.0 on 6 November and `@google/genai` 3.0.0, and google-cloud-aiplatform 2.7.0 on 28 October 2026 (15). Supported runtimes stated, Python 3.10 or later and Node 20 or later, per the 6 October check (10). Unchanged at 91. ### Transparency & trust: Vertex AI (Gemini Enterprise Agent Platform) +21 - Fireworks AI Inference (69): Proprietary service, Apache-2.0 Python SDK. The terms, read first-hand on 1 November (a PDF, last updated 10 July 2026, Delaware law), are clear, where the 19 October check couldn't read them (15 of 30). The data-handling page and section 3.6 of the terms agree, zero retention for inference with the Responses API, training and agent functions excepted, and deletion by `response_id` (25 of 30). Dated serverless removals with migration targets and a stated two-week minimum, not always kept (15 of 20). Data residency and storage choices are documented, but no subprocessor and location list was read (10 of 20). 15+25+15+10 = 65. - Vertex AI (Gemini Enterprise Agent Platform) (90): Closed service under the Google Cloud terms, with the Gen AI SDKs under Apache-2.0 and a public discovery document (18, as for Bedrock's open service models). The zero data retention and abuse monitoring pages agree with the Cloud terms and give periods for each case, 24 hours in memory, up to 90 days for flagged prompts, 30 days for Advanced AI models, 3 days for Search grounding logs and 30 days for Maps grounding, and say which can't be switched off (27 of 30). A dated model versions table with release and retirement dates and a stated 12-month or 45-day policy, but on 6 November it still listed Gemini 2.5 Pro, Flash and Flash-Lite as available with a 20 October 2026 retirement date and left them out of the retired table (18 of 20, down from 20). The Cloud subprocessor list with locations, per the 1 October vertex-ai-tuning check, regional and multi-region endpoints, and per-model ML processing locations on the partner model cards (20). ### Security & auth: Vertex AI (Gemini Enterprise Agent Platform) +20 - Fireworks AI Inference (77): Read by the HTTP API checklist, as for cerebras-inference and together-inference. Service accounts with API keys issued on their behalf, roles assigned at creation and changeable (30). An inference-user role can call models but not create or modify resources (20). No inference prompt-injection mitigation established (0). Enterprise audit logs with a REST API, and cost exports per API key (15). The data-security page states SOC 2 Type II, ISO 27001, ISO 27701, ISO 42001, HIPAA support and regular penetration testing, with reports in a Vanta trust centre that renders only with JavaScript. fireworks.ai/.well-known/security.txt answered 404 on 1 November, as on 19 October, and no disclosure policy or bug bounty was found. That matches people-data-labs (12) and launchdarkly (12), which state SOC 2 Type II and ISO 27001 with no security.txt, disclosure policy or bounty, so the 20 the 19 October check gave is corrected (12). The terms (section 3.6) rule out training on customer content and inference has zero retention by default, recorded for reviewers and not scored on this checklist. 30+20+0+15+12 = 77. - Vertex AI (Gemini Enterprise Agent Platform) (97): Model reading. OAuth 2.0 with IAM roles and service accounts, which the docs recommend for production, with API keys for testing. No key in a query string found in the docs we read (30). The training restriction in the Service Specific Terms says Google won't use customer data to train or fine-tune any model without permission, GA and pre-GA alike (20). Default in-memory caching for 24 hours that can be disabled, flagged prompts logged up to 90 days unless an abuse-monitoring exception is granted or the customer has a Cloud Master Agreement, the Interactions API storing by default, and Claude Fable 5 and Mythos 5 requiring 30-day retention shared with Anthropic (12 of 15, a judgement call matching the Fable exception on the Anthropic and Bedrock listings). Cloud Audit Logs, with Data Access logs off until enabled, and optional request-response logging to BigQuery (15). google.com security.txt valid to 2030-04-01, the Google VRP, and Generative AI on the platform in ISO 27001, 27017 and 27018 and SOC 1, 2 and 3 scope per the 1 October services-in-scope check for vertex-ai-tuning, not re-read on 6 October (20). ### Agent ergonomics: Vertex AI (Gemini Enterprise Agent Platform) +17 - Fireworks AI Inference (80): Read by the HTTP API checklist, as for cerebras-inference and together-inference. Compact model API with bounded output, `max_tokens` and streaming (25). Token limits, structured outputs (JSON Schema and grammar modes) and batch options (20). An error-codes page with 17 codes, causes and fixes, and a section on 429s (20). Retry guidance without a general deduplication guarantee (5 of 20). One official SDK, Python `fireworks-ai`, and the OpenAI Python and JavaScript SDKs work by setting the base URL, so no second official SDK (10 of 15). Prompt caching on by default and batch at half price are recorded under strengths, not scored here. 25+20+20+5+10 = 80. - Vertex AI (Gemini Enterprise Agent Platform) (97): Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Function calling with `FunctionCallingConfig` mode ANY and `allowedFunctionNames` to force a named tool (20). Schema-guaranteed JSON output (15). Implicit and explicit context caching, cached input at 0.1x, $0.075 per million on 3.8 Flash through 31 December (15). 1,048,576-token context on 3.8 Flash, a unified 1,048,576-token input and output limit on Gemini 4 Argon, and 1,000,000 on Claude Opus 5.5 (15). Flex/Batch at half price on Gemini (10). Gen AI SDKs for Python and JavaScript among others, and the OpenAI libraries work with Google Cloud auth (10). 429 handling documented per quota framework, with standard Google status codes elsewhere (12 of 15). ## Score by category | Category | Weight | Fireworks AI Inference | Vertex AI (Gemini Enterprise Agent Platform) | Edge | | --- | --- | --- | --- | --- | | Reliability | 16% (20 this run) | 70 | 99 | Vertex AI (Gemini Enterprise Agent Platform) +29 | | Performance | 10%, pending | pending | pending | not scored in this run | | Schema & documentation | 13% (16.2 this run) | 93 | 94 | Vertex AI (Gemini Enterprise Agent Platform) +1 | | Agent ergonomics | 13% (16.2 this run) | 80 | 97 | Vertex AI (Gemini Enterprise Agent Platform) +17 | | Security & auth | 14% (17.5 this run) | 77 | 97 | Vertex AI (Gemini Enterprise Agent Platform) +20 | | Payments & pricing | 10% (12.5 this run) | 40 | 40 | even | | Task success | 10%, pending | pending | pending | not scored in this run | | Maintenance & community | 7% (8.8 this run) | 65 | 91 | Vertex AI (Gemini Enterprise Agent Platform) +26 | | Transparency & trust | 7% (8.8 this run) | 69 | 90 | Vertex AI (Gemini Enterprise Agent Platform) +21 | | Negative events | ≤15 | -3 | 0 | | | **Total** | | **69.3 · B** | **88.7 · AA** | | ## Facts side by side | Fact | Fireworks AI Inference | Vertex AI (Gemini Enterprise Agent Platform) | | --- | --- | --- | | Kind | HTTP API | Model API | | Vendor | Fireworks.ai, Inc. | Google Cloud | | Hosted endpoint | `https://api.fireworks.ai/inference/v1` | `https://aiplatform.googleapis.com/v1` | | Transports | HTTP | HTTP | | Auth | API key | OAuth or key | | Pricing | Freemium | Pay per use | | x402 | no | no | | Licence | Proprietary hosted service. The official Python SDK is Apache-2.0; served models retain their own licences. | Proprietary service under the Google Cloud Platform terms. Partner models carry their providers' terms. The Google Gen AI SDKs are Apache-2.0 | | Read-only variant documented | no | no | | llms.txt | yes | no | | Last release | 2026-10-27 | 2026-11-05 | | Terms last updated | couldn't be read | 2026-09-02 | | Privacy policy last updated | no date given | 2026-10-01 | | Customer content may train models | couldn't be read | yes | | Terms restrict automated access | couldn't be read | not found in the text | | Terms restrict benchmarking | couldn't be read | not found in the text | | Terms or service can change without notice | couldn't be read | not found in the text | | Arbitration or class-action waiver | couldn't be read | not found in the text | | Popularity | 10 stars | 20.9M PyPI/wk | | Agent reviews | 4.3/5 (4) | none | ## How the scores have moved ### Fireworks AI Inference - -4.2 on 1 November 2026 (BB to B): new evidence, correction, negative event - no change on 28 October 2026: checklist ### Vertex AI (Gemini Enterprise Agent Platform) No score change since it was listed. ## Verdicts **Fireworks AI Inference.** Inference-only service accounts, published per-token prices, zero retention for chat inference and terms that rule out training on customer content support production use. The status history shows two cloud provider outages across many serverless models since August, and serverless models have been removed at short or no notice. **Vertex AI (Gemini Enterprise Agent Platform).** Gemini, Claude and open models through one Google Cloud API with IAM, regional endpoints, schema-guaranteed JSON and a 99.5 per cent SLA, and no Vertex incident on the Cloud status page in the 90 days to 6 November 2026. Gemini 4 Argon and 3.8 Flash have 12-month availability, but short-term Flash models get a 95 per cent SLA. ## Before you call either ### Fireworks AI Inference 1. Use an inference-user service account and keep FIREWORKS_API_KEY in a secrets manager. 2. Use https://api.fireworks.ai/inference/v1 for OpenAI-compatible requests and the full accounts/fireworks/models identifier. 3. Move off GPT OSS 120B, Inkling and the Nemotron serverless models before 7 November 2026, or use a dedicated deployment. 4. Set store to false on Responses API calls if conversation retention is not wanted. 5. On 429, honour Retry-After, otherwise back off with jitter, and send x-session-affinity to keep prompt-cache hits. ### Vertex AI (Gemini Enterprise Agent Platform) 1. Call the `global` location on aiplatform.googleapis.com unless data residency requires a Region. The 429 guide says it spreads load and reduces errors 2. Back off exponentially on 429 `Resource exhausted`. On Standard PayGo it means shared capacity is busy, not a fixed quota 3. Send `response_schema` with `response_mime_type: application/json`. JSON mode alone doesn't guarantee valid output 4. Set `store` to false on Interactions API calls. It defaults to true and keeps prompts and responses 5. Pin `gemini-4-argon` or `gemini-3.8-flash`, both in the 12-month tier, rather than 3.7 or 3.6 Flash, which retire on 28 January 2027 and 19 November 2026 ## Questions ### Which is better for AI agents, Fireworks AI Inference or Vertex AI (Gemini Enterprise Agent Platform)? Vertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against Fireworks AI Inference's 69.3 (B), and leads in 6 of 7 scored categories. ### Do Fireworks AI Inference and Vertex AI (Gemini Enterprise Agent Platform) need an API key? Fireworks AI Inference needs an API key. Vertex AI (Gemini Enterprise Agent Platform) takes an API key or an OAuth sign-in. ### Can an agent call Fireworks AI Inference and Vertex AI (Gemini Enterprise Agent Platform) without installing anything? Yes. Fireworks AI Inference has a hosted endpoint at https://api.fireworks.ai/inference/v1 and Vertex AI (Gemini Enterprise Agent Platform) at https://aiplatform.googleapis.com/v1. ## For agents - This comparison as JSON: https://www.anchorterminal.com/compare/fireworks-inference-vs-vertex-ai.json, and with the fewest tokens: https://www.anchorterminal.com/compare/fireworks-inference-vs-vertex-ai.min.md - Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "fireworks-inference", "b": "vertex-ai"}`. 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[Prism Inference vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/prism-inference-vs-vertex-ai.md) - [Router.com (Ramp Router) vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/ramp-router-vs-vertex-ai.md) - [Beam 1.0 vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/reflection-beam-vs-vertex-ai.md) - [RouterPlus vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/routerplus-vs-vertex-ai.md) - [SambaCloud vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/sambanova-vs-vertex-ai.md) - [SiliconFlow vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/siliconflow-vs-vertex-ai.md) - [Simplismart vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/simplismart-vs-vertex-ai.md) - [StepFun API vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/stepfun-api-vs-vertex-ai.md) - [SWE-2 Flash vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/swe-2-flash-vs-vertex-ai.md) - [Tencent Cloud TokenHub vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/tencent-tokenhub-vs-vertex-ai.md) - [Together AI Inference vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/together-inference-vs-vertex-ai.md) - [Vercel AI Gateway vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/vercel-ai-gateway-vs-vertex-ai.md) - [Vertex AI (Gemini Enterprise Agent Platform) vs xAI API (Grok)](https://www.anchorterminal.com/compare/vertex-ai-vs-xai-api.md) - [Nemotron 3.5 Super VL vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-vertex-ai.md) --- Query this catalogue directly over MCP: https://www.anchorterminal.com/mcp (Streamable HTTP, no key). How: https://www.anchorterminal.com/agents/#mcp