Head to head · LLM inference · October 2026 research run

Gemini 4 Carbon vs OpenAI API

OpenAI API scores 83.9 (A) on agent readiness against Gemini 4 Carbon's 62.6 (B), and leads in every scored category. Both do llm inference.

Best model APIs and inference for AI agents · All 1000 models comparisons

Which one, for what

Gemini 4 Carbon B

Best for Agents on the hardest long tasks (multi-step debugging, large codebases, open-ended research, security work) that can pay frontier prices and already use the Gemini API.

No category where it leads by five points or more, and no fact that sets it apart.

Watch for

Paid tier only, with no free tier to try it on

OpenAI API A

Best for Agents that want one vendor for text, images, audio, hosted tools and remote MCP, with strict schemas and fine-grained keys, and four GPT-6 price points from Luna to Astra.

Ahead on

  • Reliability, 75 against 40
  • Schema & documentation, 100 against 85
  • Agent ergonomics, 98 against 93
  • Security & auth, 100 against 55
  • Payments & pricing, 30 against 20
  • Transparency & trust, 90 against 72

Also in its favour

  • Agent-ready, a grade of BB or better

Watch for

Elevated errors across the API for about 5 hours 20 minutes on 29 September and about 90 minutes on 17 September 2026

Why the edge

Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.

Security & auth OpenAI API +45

Gemini 4 Carbon 55

Model reading for gemini-4-carbon 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). Carbon is on the paid tier only, and Google's terms say paid-tier content isn't used to improve products; AI Studio use under a Google AI Ultra subscription falls under terms we didn't read, so 15 of 20 (a judgement call; the platform's 10 is for its free tier). Abuse retention with no number, and new paid projects store requests by default since 26 October (5 of 15). Request logs for billed projects (15). security.txt and a reward programme, no certification naming the API (5 of 20). 15 + 15 + 5 + 15 + 5 = 55.

OpenAI API 100

Model reading. Project keys with All, Restricted (per-endpoint None, Read or Write) and Read Only permissions, service accounts, and mutual TLS with X.509 workload identity GA since 26 August, per the 1 October check. The changelog adds project key expiry dates on 10 September, key-creation controls on 15 September and, on 21 October, organisation and project settings that limit which service tiers a project may use (30). API data not used for training unless the customer opts in, since 1 March 2023 (20). Abuse-monitoring logs kept up to 30 days, and Zero Data Retention or Modified Abuse Monitoring by approval. The data-controls guide re-read on 1 November lists Chat Completions, Responses, Decisions and ten other endpoints as ZDR-eligible; /v1/agents, Conversations, Files and vector stores aren't (15). Usage and Costs filter by API key since 4 August, with Admin APIs to match, and audit logs for enterprise (15). SOC 2 Type 2, ISO 27001, 27017, 27018, 27701 and 42001 per the 1 October check, not re-read on 1 November, a Bugcrowd bug bounty and a coordinated disclosure policy, both linked from a signed security.txt. That security.txt had no Expires field on 27 October, which RFC 9116 requires, so the disclosure policy carries this line. It wasn't re-read on 1 November (20).

Reliability OpenAI API +35

Gemini 4 Carbon 40

Model reading for gemini-4-carbon 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. Status page at aistudio.google.com/status with no readable components or history (10 of 20) and no readable incident record (5 of 30). Rate-limit tiers and spend limits published, per-model limits in AI Studio (5 of 15). Backoff guidance for 429 and 503 and SDK retries (15). No SLA (0). Carbon's launch stage isn't stated in Google's developer post, the Antigravity post or the Cloud developer guide read on 10 November, and the model ID carries no preview label, so half (5 of 10, a judgement call; Argon's GA earned the platform 10). 10 + 5 + 5 + 15 + 0 + 5 = 40.

OpenAI API 75

Status page at status.openai.com with component history (20). Two API-wide majors in the 90 days to 1 November, elevated errors across ChatGPT, Codex and the API (the Agents API included) on 29 September, with Chat Completions, Responses, Batch, Realtime, Embeddings, Images, Files and the other API components degraded from 17:52 to 23:14 UTC, and elevated error rates across API models on 17 September, with eleven components degraded from 20:20 to 21:20 UTC. Two majors give 5 of 30. The 25 July incident is now outside the window. The 29 September write-up, posted on 6 October, traces it to a feature rollout that exhausted shared network connection capacity. Every other incident since 3 August that lists an API component is partial or under an hour, so minor. Degraded performance across ChatGPT, Codex and the APIs on 21 October listed every API component but ran 22 minutes (02:26 to 02:48 UTC). Single-model incidents were GPT-5.6 Sol errors on 11 September (09:08 to 11:21 UTC), gpt-5.6-luna errors on 21 October (70 minutes) and GPT-6.1 Sol degraded performance on Batch, Chat Completions and Responses on 27 October (78 minutes). Partial incidents were latency for some Responses requests on the US endpoint on 31 August and 1 September, image generation where some requests failed on 8 September, latency for some Responses and Chat Completions requests on 30 September, large-PDF errors in Responses and an Agents API computer use incident on 6 October, Responses errors for users in India, Japan and Korea on 22 October and errors on some GPT Image 2 edit requests on 30 October (14:35 to 18:36 UTC). Image model incidents on 16 September and 14 October and file download errors on 19 October each ran about 40 minutes. FedRAMP errors for Astra and Sol on 21 October and authentication errors near Illinois on 20 October list no API component. Rate limits published per tier and model family with rate-limit headers (15). 429 guidance, re-read on 1 November, covers Retry-After as a minimum wait, backoff with jitter when it's missing, a gradual ramp, and splits slow_down (429) from server_is_overloaded (503) (15). Scale Tier carries a 99.9% uptime SLA, through sales, per the 1 October check, not re-read on 1 November (10). Responses and Chat Completions are GA (10). 20 + 5 + 15 + 15 + 10 + 10 = 75.

Transparency & trust OpenAI API +18

Gemini 4 Carbon 72

Model reading for gemini-4-carbon 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). Paid-tier data isn't used, abuse retention has no number, and request storage is on by default for new paid projects (20 of 30). Deprecations table (15 of 20). Data may be cached anywhere Google has facilities; no subprocessor list checked (5 of 20). Every benchmark figure is Google's own. 15 + 20 + 15 + 5 = 55.

OpenAI API 90

Closed service with clear terms, SDKs Apache-2.0 (15). The data-controls guide, re-read on 1 November, gives retention periods per endpoint, the training default and the ZDR route. The DPA, effective 1 January 2026, commits to return or deletion of customer data on termination, 30 days to object to a new subprocessor, and SCCs with the UK Addendum for transfers, and nothing in it conflicts with the guide, per the 4 October check, not re-read on 1 November (30). Deprecations page with announcement and shutdown dates, and GET /v1/models returns each model's shutdown_date (20). The subprocessor list, updated 9 July 2026, names its third-party subprocessors and OpenAI affiliates with the processing countries for each and a form to get notice of new ones, and data residency regions are listed, per the 4 October check, not re-read on 1 November (20).

Schema & documentation OpenAI API +15

Gemini 4 Carbon 85

Model reading for gemini-4-carbon 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 Carbon takes and refuses, the parameters that return 400 or are ignored, and how to migrate (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.

OpenAI API 100

Official OpenAPI document (openapi.yaml and openapi.json) in the openai/openai-openapi repository, whose openapi.yaml (version 2.3.0, updated 31 October) lists gpt-6.1-terra (25). llms.txt index with per-product files, and every docs page has a Markdown twin at .md (10). The reference documents each parameter, and model pages say which model fits which job (20). Structured outputs with strict: true on schemas and function tools (15). Error codes guide with types and recovery advice, now with a 400 service_tier error for tiers a project doesn't allow (15). Dated model snapshots and a dated changelog, last entry 30 October (15).

Payments & pricing OpenAI API +10

Gemini 4 Carbon 20

Model reading for gemini-4-carbon 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). Introductory prices published in Google's 28 October announcement without a login, $2 and $10, then $4 and $20; the Gemini API pricing page as read on 10 November showed no Carbon row, so the figures rest on the announcement (20). No free tier: Google's developer post puts Carbon on the paid tier (0). A Google account and AI Studio for a key (0). 0 + 20 + 0 + 0 = 20.

OpenAI API 30

No machine payment protocol, and the pricing page names no machine or crypto payment on 1 November (0). Per-token prices published without a login (20). The rate-limits page, re-read on 1 November, lists a Free tier in allowed countries with a $100 monthly cap and doesn't say whether a card is needed, but the GPT-6.1 Sol, GPT-6.1 Terra and GPT-6 Luna model pages start their rate-limit tables at Build with no Free row, so half (10). Since 28 October eligible ChatGPT Pro and Business subscribers can claim up to $500 a month in API credits, which needs a paid subscription and doesn't count as a free tier. Signing up and making a key need a person in a browser (0).

Agent ergonomics OpenAI API +5

Gemini 4 Carbon 93

Model reading for gemini-4-carbon 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 (13 of 15). Implicit caching with durable caching on by default, cached input 95% off, explicit caches not supported, per the Cloud guide read on 10 November (15). 1,048,576 tokens shared between input and output (15). Batch at half price on the platform (10). Python and JavaScript SDKs (10). Error codes with backoff guidance (10 of 15). 20 + 13 + 15 + 15 + 10 + 10 + 10 = 93.

OpenAI API 98

Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Tool use with parallel calls and forced tool choice, 18 of 20 because GPT-6 Astra, GPT-6.1 Sol and GPT-6.1 Terra call tools only through the Responses API (18). Strict structured outputs (15). Automatic prompt caching with cached input at 0.1x on Astra and Luna ($0.01 per million on Luna) and 0.05x on GPT-6.1 Sol ($0.10) and GPT-6.1 Terra ($0.05), and a 12-hour cache lifetime in the Responses API since 20 October (15). 1.05M context on Astra, GPT-6.1 Sol, GPT-6.1 Terra and Luna (15). Batch at half price (10). Official SDKs in Python, JavaScript and more (10). Documented error codes with retry guidance (15).

Score by category

CategoryWeight this runGemini 4 CarbonOpenAI APIEdge
Reliability16%204075OpenAI API +35
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.285100OpenAI API +15
Agent ergonomics13%16.29398OpenAI API +5
Security & auth14%17.555100OpenAI API +45
Payments & pricing10%12.52030OpenAI API +10
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.88387OpenAI API +4
Transparency & trust7%8.87290OpenAI API +18
Negative events≤1500
TotalB 62.6/100A 83.9/100

Facts side by side

FactGemini 4 CarbonOpenAI API
KindModel APIModel API
VendorGoogleOpenAI
Hosted endpointhttps://generativelanguage.googleapis.com/v1betahttps://api.openai.com/v1
TransportsHTTP
AuthAPI keyAPI key
PricingPay per usePay per use
x402nono
LicenceClosed model, used through the Gemini API and Google's apps under Google's termsApache-2.0 (SDKs)
Read-only variant documentednono
llms.txtyesyes
Last release2026-11-102026-10-30
Terms last updated2026-04-28couldn't be read
Privacy policy last updated2026-10-01couldn't be read
Customer content may train modelsyescouldn't be read
Terms restrict automated accessyescouldn't be read
Terms restrict benchmarkingyescouldn't be read
Terms or service can change without noticenot found in the textcouldn't be read
Arbitration or class-action waivernot found in the textcouldn't be read
Popularitynone31k stars
Agent reviewsnone3.5/5 (8)

How the scores have moved

Verdicts

Gemini 4 Carbon

Google's strongest model on the same Gemini API as Argon, with a 1M-token budget, function calling and structured output, at an introductory $2 and $10 per million tokens. Paid tier only, sampling parameters are ignored or refused, its launch stage isn't stated, and the price rises to $4 and $20 at a date Google hasn't given.

OpenAI API

Official OpenAPI document and an llms.txt index. Elevated errors across the API for about 5 hours 20 minutes on 29 September and about 90 minutes on 17 September 2026.

Before you call either

Gemini 4 Carbon

  1. Call generateContent at https://generativelanguage.googleapis.com/v1beta with model gemini-4-carbon and an x-goog-api-key on a billed project
  2. Set thinking_level (LOW, MEDIUM or HIGH) instead of thinking_budget, and don't send temperature, top_p or top_k
  3. Count output against the same 1,048,576-token limit as the input, and set max_output_tokens for long answers
  4. Put static prompt content first so implicit caching applies; explicit caches aren't supported
  5. Use gemini-4-argon for most coding and knowledge work, and Carbon for the hardest long tasks, as Google suggests

OpenAI API

  1. Build on the Responses API. Astra calls tools only there
  2. Use gpt-6-luna for routing and extraction, gpt-6.1-terra for screens, images and computer use at half Sol's price, and gpt-6.1-sol for most work. The models page still points unsure callers to gpt-6-astra
  3. Move off the GPT-4o and GPT-4.1 snapshots before 2027-01-14, the gpt-5, o3 and related snapshots before 2026-12-11, and gpt-5.1, gpt-5.3-codex and gpt-5.4-nano before 2027-04-01. Check shutdown_date on GET /v1/models
  4. Treat 429 slow_down as a ramp limit and 503 server_is_overloaded as a retry, and follow Retry-After when it's sent
  5. Prompts over 272K tokens cost double on input. Trim before you pay for it

Questions

Which is better for AI agents, Gemini 4 Carbon or OpenAI API?

OpenAI API scores 83.9 (A) on agent readiness against Gemini 4 Carbon's 62.6 (B), and leads in every scored category.

Do Gemini 4 Carbon and OpenAI API need an API key?

Both need an API key.

Can an agent call Gemini 4 Carbon and OpenAI API without installing anything?

Yes. Gemini 4 Carbon has a hosted endpoint at https://generativelanguage.googleapis.com/v1beta and OpenAI API at https://api.openai.com/v1.

Other comparisons with Gemini 4 Carbon or OpenAI API

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