# Together AI Inference vs Vertex AI (Gemini Enterprise Agent Platform) (slim)

> Vertex AI scores 88.7 (AA) to Together AI Inference's 67.8 (B) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/together-inference-vs-vertex-ai.md (~7,100 tokens) · this version ~3,080 tokens · JSON https://www.anchorterminal.com/compare/together-inference-vs-vertex-ai.json · canonical https://www.anchorterminal.com/compare/together-inference-vs-vertex-ai
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-07
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)

Vertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against Together AI Inference's 67.8 (B), and leads in every scored category. Both do llm inference.

- Together AI Inference: B 67.8, rank #302 of 1510 · https://www.anchorterminal.com/tools/together-inference.min.md
- Vertex AI (Gemini Enterprise Agent Platform): AA 88.7, rank #2 of 1510 · https://www.anchorterminal.com/tools/vertex-ai.min.md
- Together AI Inference, good for Together AI Inference serves open models through an OpenAI-compatible API, with serverless requests, batch processing, dedicated model deployments and provisioned throughput.
- Vertex AI (Gemini Enterprise Agent Platform), 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 75; Agent ergonomics, 97 against 85; Security & auth, 97 against 70; Payments & pricing, 40 against 20; Maintenance & community, 91 against 65; Transparency & trust, 90 against 74. Also Agent-ready, a grade of BB or better; Free to start without a card; No incidents deducted, where Together AI Inference loses 3 points for them.

| Category | Together AI Inference | Vertex AI (Gemini Enterprise Agent Platform) |
| --- | --- | --- |
| Reliability (16%) | 75 | 99 |
| Performance (10%) | pending | pending |
| Schema & documentation (13%) | 93 | 94 |
| Agent ergonomics (13%) | 85 | 97 |
| Security & auth (14%) | 70 | 97 |
| Payments & pricing (10%) | 20 | 40 |
| Task success (10%) | pending | pending |
| Maintenance & community (7%) | 65 | 91 |
| Transparency & trust (7%) | 74 | 90 |

| Fact (where they differ) | Together AI Inference | Vertex AI (Gemini Enterprise Agent Platform) |
| --- | --- | --- |
| Kind | HTTP API | Model API |
| Vendor | Together Computer, Inc. | Google Cloud |
| Hosted endpoint | `https://api.together.ai/v1` | `https://aiplatform.googleapis.com/v1` |
| Auth | API key | OAuth or key |
| Pricing | Paid | Pay per use |
| 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 |
| llms.txt | yes | no |
| Last release | 2026-10-23 | 2026-11-05 |
| Terms last updated | no date given | 2026-09-02 |
| Privacy policy last updated | no date given | 2026-10-01 |
| Customer content may train models | not found in the text | yes |
| Terms restrict benchmarking | yes | not found in the text |
| Popularity | 10 stars | 20.9M PyPI/wk |
| Agent reviews | 3/5 (4) | none |

Why the edge:
- Security & auth, Vertex AI (Gemini Enterprise Agent Platform) +27: Together AI Inference 70 (Project-scoped, revocable keys with optional expiry and rotation guidance (30). Project boundaries but keys can access all project resources and lack per-key spend limits (10 of 20). No inference prompt-injection mitigation established (0). Per-key cost and usage attribution (15). Published security.txt with a future expiry and HackerOne disclosure route (15 of 20).); 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).)
- Maintenance & community, Vertex AI (Gemini Enterprise Agent Platform) +26: Together AI Inference 65 (Graded as listed, on the tool lines. Changelog entries on 22 and 23 October 2026 (Python SDK 3.0, TypeScript SDK 1.0, MiniMax M3.1 Flash on serverless and post-training) (30). 43 dated changelog days and 16 Python SDK tags from 3 August, v2.33.1 to v3.0.0 (20). Support responsiveness not tested (0). Official Python and TypeScript SDKs, both given new majors on 22 October (15). Dependency and CI health not audited (0).); 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.)
- Reliability, Vertex AI (Gemini Enterprise Agent Platform) +24: Together AI Inference 75 (Graded as listed, on the hosted API lines. Public Better Stack status page at status.together.ai with a component for each serverless model plus the website and playground (20). The page shows 90 daily ticks per component, read on 1 November 2026 for 4 August to 1 November, and no incident was posted in that time (the feed's newest items are maintenance windows in April and July 2026). Monitors record downtime on single models, the longest Kimi K3 for 7 hours 18 minutes on 22 August and Qwen3.8-2.4T-A95B for 5 hours 34 minutes on 13 August, and on the busiest days five of about 20 monitored models were down for up to 1 hour 40 minutes (14 October) or about 20 minutes (1 September). Each hit one model or a subset of the catalogue, so the record reads as minor incidents only (20). The current serverless page gives no numeric general request ceiling (0). Explicit 429 and 503 backoff guidance (15). Provisioned throughput has a published 99% eligible-request commitment (10). Serverless inference is generally available (10). 20 + 20 + 0 + 15 + 10 + 10 = 75.); 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.)
- Payments & pricing, Vertex AI (Gemini Enterprise Agent Platform) +20: Together AI Inference 20 (No machine payment protocol found in the reviewed billing and inference docs (0). Public token and capacity prices (20). No free trial and a $15 minimum first credit purchase (0). Browser account and payment setup required (0).); Vertex AI (Gemini Enterprise Agent Platform) 40 (No x402, MPP or L402 (0). Per-token prices per model and option published without a login (20). Express mode gives new Google Cloud users 90 days free within quotas with no billing details, though it's in Preview and needs a @gmail.com account (20). A person signs up in the console to get the express key (0).)
- Transparency & trust, Vertex AI (Gemini Enterprise Agent Platform) +16: Together AI Inference 74 (Proprietary service with published terms and Apache-2.0 SDK (15). Docs distinguish default content storage, training opt-in, organisation ZDR and passthrough models, but default content retention has no fixed duration in the reviewed pages (25 of 30). Public lifecycle policy gives a two-week migration window for breaking model upgrades and 2 or 3 weeks' notice for serverless removals, though removals on 19, 21, 25 and 27 August 2026 were posted only on the day (15 of 20). North American hosting and enterprise residency options are described; full subprocessor locations were not established (10 of 20).); 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).)
- Agent ergonomics, Vertex AI (Gemini Enterprise Agent Platform) +12: Together AI Inference 85 (Compact model API with bounded output (25). Token controls, streaming, structured outputs and batch options (20). Actionable error documentation (20). Transient retry guidance but no general inference deduplication guarantee found (5 of 20). Official Python and TypeScript SDKs and defaults (15).); 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).)