Gemini 4 Carbon vs GPT-5-Codex
Full profiles: Gemini 4 Carbon (Google) and GPT-5-Codex (OpenAI): every benchmark, price and rank.
Updated · Data from 4 sources
As of 29 Oct 2026, Gemini 4 Carbon is ahead of GPT-5-Codex on quality (65.1 vs 58.6 on the BenchLeader Index), but GPT-5-Codex is 2.3× cheaper at $3.44 vs $8.00 per 1M tokens blended. Gemini 4 Carbon leads in every category we measure both in. GPT-5-Codex streams ~2× faster.
Key facts (as of 29 Oct 2026)
- Gemini 4 Carbon scores 65.1 on the BenchLeader Index and GPT-5-Codex scores 58.6 (BenchLeader, 29 Oct 2026).
- Gemini 4 Carbon costs $8.00 per 1M tokens blended (list price, 29 Oct 2026).
- GPT-5-Codex costs $3.44 per 1M tokens blended (list price, 29 Oct 2026).
- GPT-5-Codex streams ~2× faster than Gemini 4 Carbon (Artificial Analysis, 7-day median, 29 Oct 2026).
- Of the 4 benchmarks both models have, Gemini 4 Carbon leads 4 (BenchLeader, 29 Oct 2026).
Gemini 4 Carbon benchmarks high Google
GPT-5-Codex benchmarks high OpenAIOpen in the comparison toolWhich to pick for…
The pick's numbers come first. Category scores on the BenchLeader scale (50 is the average model, 15 points one standard deviation). High confidence means a lead of half a standard deviation or more; under one point is called either.
| Use case | Pick | Why | Confidence |
|---|---|---|---|
| Coding | Gemini 4 Carbon | 72 vs 59 category score | High |
| Long documents | Gemini 4 Carbon | 65 vs 61 category score; AA-LCR v1.1 79.3% vs 71.7% | Medium |
| Lowest cost | GPT-5-Codex | $3.44 vs $8.00 per 1M blended; agentic coding session $0.115 vs $0.320 | – |
| Fastest first answer | GPT-5-Codex | 9.2 s (GPT-5-Codex (high)) vs 103.1 s (Gemini 4 Carbon (high)) to the first answer token | – |
| High volume on a budget | Neither flagship | A smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs | – |
Key differences
- Gemini 4 Carbon (high) leads on quality: 65.1 vs 58.6.
- Gemini 4 Carbon (high) is stronger in coding, knowledge, long context, reasoning.
- GPT-5-Codex (high) is stronger in agents & tools, instruction following, multimodal.
- GPT-5-Codex (high) is 2.3× cheaper ($3.44 vs $8.00 per 1M blended).
- GPT-5-Codex (high) streams 2.1× faster (211 vs 100 tokens per second).
At a glance
| Spec | Gemini 4 Carbon | GPT-5-Codex |
|---|---|---|
| Developer | OpenAI | |
| Released | 28 Oct 2026 | 15 Sept 2025 |
| Context window (tokens) | 1,000,000 | 400,000 |
| Compared at | Gemini 4 Carbon (high) | GPT-5-Codex (high) |
| Open weights | No | No |
| Price in / out / cached input per 1M | $4.00 / $20.00 / – | $1.25 / $10.00 / $0.125 |
Category by category
Category scores on the BenchLeader scale: 50 is the average evaluated model, 15 points is one standard deviation. A gap under one point is called level.
| Category | Gemini 4 Carbon (high) | GPT-5-Codex (high) | Leader |
|---|---|---|---|
| Reasoning | 78.9 | – | not comparable |
| Coding | 71.7 | 58.5 | Gemini 4 Carbon |
| Agents & tools | – | 66.8 | not comparable |
| Knowledge | 75.8 | – | not comparable |
| Instruction following | – | 72.4 | not comparable |
| Multimodal | – | 56.4 | not comparable |
| Long context | 64.5 | 60.5 | Gemini 4 Carbon |
Where sources disagree
Across the 4 benchmarks both have, Gemini 4 Carbon leads 4, GPT-5-Codex leads 0. Every overall index that rates both puts Gemini 4 Carbon ahead.
| Overall index | Gemini 4 Carbon (high) | GPT-5-Codex (high) | Leader |
|---|---|---|---|
| BenchLeader Index | 65.1 | 58.6 | Gemini 4 Carbon |
Each publisher runs its own tasks, harnesses and effort settings, so their overall verdicts can differ; BenchLeader reconciles them on one scale. † measured at another effort setting of the same model (the publisher did not test the one compared here).
Price, speed and latency
List prices blended at three input tokens per output token. Per-task prices use the token counts on the methodology page; suite cost is what Artificial Analysis paid to run its whole Intelligence Index.
| Measure | Gemini 4 Carbon (high) | GPT-5-Codex (high) |
|---|---|---|
| Blended price per 1M tokens | $8.00 | $3.44 |
| Input / output per 1M | $4.00 / $20.00 | $1.25 / $10.00 |
| Cached input per 1M | – | $0.125 |
| Price per task: chat reply | $0.0076 | $0.0035 |
| Price per task: summarize a 30-page report | $0.060 | $0.021 |
| Price per task: code edit | $0.054 | $0.022 |
| Price per task: agentic coding session | $0.320 | $0.115 |
| Price per task: structured extraction | $0.012 | $0.0045 |
| Cost to run a full benchmark suite | $7.76 | – |
| Output speed | 100 tok/s | 211 tok/s |
| Time to first answer | 103.1 s | 9.2 s |
| Time to a complete answer | 108.1 s | 11.6 s |
Each model is compared at its best-ranked reasoning-effort setting. Gemini 4 Carbon (high) scores 65.1 and takes 103 s to its first answer token. GPT-5-Codex (high) scores 58.6 and takes 9 s to its first answer token. Higher effort means more thinking before the answer: better scores, longer waits and more tokens billed. How reasoning effort changes scores and cost.
Every benchmark
39 benchmarks, grouped by category; each name links to the board and its leaders. † measured at another effort setting of the same model, shown for reference and not counted as a win.
| Metric | Publisher | Gemini 4 Carbon (high) | GPT-5-Codex (high) |
|---|---|---|---|
| BenchLeader Index | BenchLeader | 65.1 | 58.6 |
| Coding score | BenchLeader | 71.7 | 58.5 |
| Knowledge score | BenchLeader | 75.8 | – |
| Long context score | BenchLeader | 64.5 | 60.5 |
| Reasoning score | BenchLeader | 78.9 | – |
| Agents & tools score | BenchLeader | – | 66.8 |
| Instruction following score | BenchLeader | – | 72.4 |
| Multimodal score | BenchLeader | – | 56.4 |
| Blended price $/M | BenchLeader | $8.00 | $3.44 |
| Output speed | BenchLeader | 100 tok/s | 211 tok/s |
| Time to first answer | BenchLeader | 103.1 s | 9.2 s |
| Context window | BenchLeader | 1,000,000 tokens | 400,000 tokens |
| Reasoning | |||
| GPQA Diamond (AA) | Artificial Analysis | – | 83.7% |
| Humanity's Last Exam (AA) | Artificial Analysis | 60.4% | 27.9% |
| HLE-Diamond (AA) | Artificial Analysis | 69.1% | – |
| Kagi LLM Benchmark | Kagi LLM Benchmark | – | 70.3%† |
| CritPt | Artificial Analysis | 36.0% | 5.1% |
| CritPt v2 hard subset (AA) | Artificial Analysis | 63.0% | – |
| Coding | |||
| SciCode | SciCode | 64.2% | – |
| WeirdML | WeirdML | – | 54.5% |
| LiveCodeBench | Vals AI | – | 84.7% |
| Vibe Code Bench v1.1 | Vals AI | 89.1% | – |
| Terminal-Bench 4.0 (AA) | Artificial Analysis | 65.2% | – |
| FrontierCode 1.1 (AA) | Artificial Analysis | 48.5% | – |
| FrontierCode 2.0 (AA) | Artificial Analysis | 40.6% | – |
| Agents & tools | |||
| Terminal-Bench | Terminal-Bench | – | 44.3%† |
| Terminal-Bench Hard | Artificial Analysis | – | 37.9% |
| τ²-Bench Telecom (AA) | Artificial Analysis | – | 86.8% |
| Finance Agent v2.1 | Vals AI | 67.2% | – |
| Harvey's Legal Agent Benchmark v1.1 | Vals AI | 17.5% | – |
| Legal Research Bench | Vals AI | 55.8% | – |
| Tax Agent Bench | Vals AI | 48.9% | – |
| Terminal-Bench 4.0 (Vals) | Vals AI | 63.1% | – |
| Vending-Bench 2 | Andon Labs | 16484.2† | – |
| AutomationBench | Artificial Analysis | 77.8% | – |
| GDP.pdf (AA) | Artificial Analysis | 28.4% | – |
| AA-Briefcase v1.1 | Artificial Analysis | 1609 | – |
Show all 39 benchmarks
| Metric | Publisher | Gemini 4 Carbon (high) | GPT-5-Codex (high) |
|---|---|---|---|
| Agents & tools | |||
| Terminal-Bench-Science 0.1 (AA) | Artificial Analysis | 64.8% | – |
| Knowledge | |||
| AA-Omniscience v1.1 | Artificial Analysis | 53.5 | – |
| Excel Modeling Benchmark v1.1 | Vals AI | 76.5% | – |
| AA-Omniscience v1.1: accuracy | Artificial Analysis | 58.3% | – |
| AA-Omniscience v1.1: non-hallucination | Artificial Analysis | 88.6% | – |
| Instruction following | |||
| IFBench | Artificial Analysis | – | 74.2% |
| Multimodal | |||
| MMMU-Pro | Artificial Analysis | – | 73.8% |
| Blueprint-Bench 2 | Epoch AI Benchmarking Hub | 58.6%† | – |
| Long context | |||
| AA-LCR v1.1 | Artificial Analysis | 79.3% | 71.7% |
| Composite | |||
| AA Intelligence Index v5.0 | Artificial Analysis | 59.4 | – |
| AA Intelligence Index v4.3.2 | Artificial Analysis | – | 24.9 |
| AA Progress Index v1 | Artificial Analysis | 351.6 | 275.1 |
| Vals Index | Vals AI | 70.4 | – |
| Vals Finance Index | Vals AI | 66.3% | – |
Data as of 2026-10-29. Best configuration of each model; every score links to its source on the model pages.
What changed
- GPT-5-Codex (high): 1 new result (AA Progress Index v1).
- GPT-5-Codex (high): BenchLeader Index 59.0 → 58.4.
Related comparisons
- Gemini 4 Carbon vs Claude Opus 5.5
- Gemini 4 Carbon vs GPT-6 Astra
- Gemini 4 Carbon vs GPT-6.1 Sol
- GPT-5-Codex vs Claude Opus 5.5
- GPT-5-Codex vs GPT-6 Astra
- GPT-5-Codex vs GPT-6.1 Sol
- GPT-5-Codex vs Claude Fable 5.1
- Gemini 4 Argon vs GPT-5-Codex
Rankings: Best LLM overall · Best LLM for coding · Best LLM for agents · Best cheap LLMs
Gemini 4 Carbon vs GPT-5-Codex: questions
- Is Gemini 4 Carbon better than GPT-5-Codex?
- Gemini 4 Carbon (high) leads on quality: 65.1 vs 58.6. The BenchLeader Index combines every independent quality benchmark; Gemini 4 Carbon (high) is ahead overall as of 29 Oct 2026, but check the category scores for your use.
- Gemini 4 Carbon vs GPT-5-Codex: which is cheaper, and will that change?
- GPT-5-Codex is cheaper today: $3.44 against $8.00 per million tokens, blended at three input tokens per output token. No price change has been announced for either.
- Is Gemini 4 Carbon or GPT-5-Codex better for coding?
- Gemini 4 Carbon scores higher in coding (72 vs 59 on the category index, where 50 is average).
- Which is faster, Gemini 4 Carbon or GPT-5-Codex?
- GPT-5-Codex streams ~2× faster (211 vs 100 output tokens per second, Artificial Analysis 7-day median).
- Which is better for long documents?
- Gemini 4 Carbon scores higher on long-context benchmarks (65 vs 61). Gemini 4 Carbon accepts more context: 1,000,000 against 400,000 tokens for GPT-5-Codex.
More questions (3)
- Which has lower latency?
- GPT-5-Codex answers first: 9.2 s against 103.1 s to the first answer token, as Artificial Analysis measures it. Reasoning effort drives most of this: a higher setting thinks longer before it answers.
- Do independent benchmarks agree on Gemini 4 Carbon vs GPT-5-Codex?
- Across the 4 benchmarks both have, Gemini 4 Carbon leads 4, GPT-5-Codex leads 0. Every overall index that rates both puts Gemini 4 Carbon ahead.
- When was Gemini 4 Carbon released?
- Gemini 4 Carbon was released on 28 Oct 2026.