OpenAI, proprietary
GPT-5
GPT-5 by OpenAI ranks 45th of 354 ranked models on the Noometry Index as of October 2026, with a score of 50.9. Its strongest category is long context, where it ranks 2nd. API pricing starts at $1.25 per million input tokens and $10 per million output tokens, with a 400K-token context window.
Last verified
Specifications
- Noometry rank
- #45 of 354
- Index score
- 50.9
- Evidence
- Confirmed 69 results
- Provider
- OpenAI
- Released
- August 7, 2025
- Weights
- Proprietary
- Reasoning
- Yes
- Context window
- 400K
- Max output
- 128K
- Input price
- $1.25 / M
- Output price
- $10 / M
- Blended price
- $3.44 / M
- Output speed
- 2 tokens/s Kagi
- Value
- #164 of 219
- Knowledge cutoff
- September 2024
- Input
- text, image
Category scores
Each category score combines every public result we have in that category.
- Coding 50.3
- Agentic & Tool Use 33.1
- Reasoning 38.3
- Math 55.0
- Knowledge 56.6
- Multimodal 46.8
- Multilingual 51.4
- Instruction Following 73.8
- Long Context 69.5
- Writing & Preference 63.4
| Category | Score | Rank | Results |
|---|---|---|---|
| Coding | 50.3 | #47 | 8 |
| Agentic & Tool Use | 33.1 | #56 | 5 |
| Reasoning | 38.3 | #64 | 12 |
| Math | 55.0 | #44 | 7 |
| Knowledge | 56.6 | #43 | 8 |
| Multimodal | 46.8 | #13 | 3 |
| Multilingual | 51.4 | #110 | 1 |
| Instruction Following | 73.8 | #113 | 2 |
| Long Context | 69.5 | #2 | 2 |
| Writing & Preference | 63.4 | #65 | 6 |
Strengths and weaknesses
Categories where GPT-5 places highest and lowest among the models ranked in each, with its score against that category's median.
Strongest categories
| Category | Score | vs median | Rank |
|---|---|---|---|
| Long Context | 69.5 | +28.6 | #2 of 296, top 1% |
| Multimodal | 46.8 | +8.3 | #13 of 128, top 11% |
| Math | 55.0 | +18.4 | #44 of 327, top 14% |
Weakest categories
| Category | Score | vs median | Rank |
|---|---|---|---|
| Instruction Following | 73.8 | +2.6 | #113 of 305, top 38% |
| Multilingual | 51.4 | +3.9 | #110 of 297, top 38% |
| Agentic & Tool Use | 33.1 | +2.7 | #56 of 154, top 37% |
Closest competitors
The models ranked just above and below GPT-5. When scores are this close, price and speed are often the better way to choose.
| Model | Rank | Score | Blended $/M | Speed | |
|---|---|---|---|---|---|
| GLM-5.3-Flash | #41 | 51.8 | $0.24 | — | Compare |
| Qwen3.7 Max | #42 | 51.5 | $3.75 | — | Compare |
| Qwen3.6 Max Preview | #43 | 51.5 | $2.92 | — | Compare |
| GLM-5.2 | #44 | 51.1 | $2.15 | 23 | Compare |
| Muse Spark | #46 | 50.6 | — | — | Compare |
| Claude Opus 4.5 | #47 | 50.5 | $10 | 13 | Compare |
| Muse Spark 1.2 | #48 | 50.3 | $2 | — | Compare |
| MiMo-V2.6-Pro | #49 | 50.3 | $0.54 | — | Compare |
Sponsored placements are available on pages like this one. Advertise on Noometry
Benchmark results
Every published result we track, with its source. Bold rows are the ones used for ranking; where several exist we prefer independent runs over self-reported numbers.
Coding
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| SWE-bench Verified | 73.6% | #19 of 32, top 60% | high | Epoch AI | 2026-02-06 |
| SWE-bench Verified | 71.5% | medium | Epoch AI | 2026-02-05 | |
| SWE-bench Verified (bash only) | 65% | #16 of 39, top 42% | medium | SWE-bench | 2025-08-07 |
| Aider Polyglot | 88% | Best of 44 | high | Epoch AI | |
| Aider Polyglot | 81.3% | low | Epoch AI | ||
| Aider Polyglot | 86.7% | medium | Epoch AI | ||
| LMArena WebDev | 1418 | #65 of 113, top 58% | medium | LMArena | 2026-10-08 |
| SciCode | 42.9% | #67 of 121, top 56% | Epoch AI | ||
| GSO | 6.9% | #20 of 31, top 65% | high | Epoch AI | |
| WeirdML | 39.8% | Epoch AI | |||
| WeirdML | 60.7% | #30 of 119, top 26% | high | Epoch AI | |
| LMArena Coding | 1398 | LMArena | 2026-10-08 | ||
| LMArena Coding | 1436 | #102 of 294, top 35% | high | LMArena | 2026-10-08 |
| ALE-Bench | 1,162 | #34 of 105, top 33% | high | Epoch AI | |
| ALE-Bench | 807.65 | minimal | Epoch AI | ||
| AlgoTune | 1.67 | #8 of 18, top 45% | high | Epoch AI |
Agentic & Tool Use
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| Terminal-Bench | 49.6% | #17 of 41, top 42% | Epoch AI | ||
| Terminal-Bench | 49.6% | medium | Epoch AI | ||
| GDPval | 34.8% | #6 of 11, top 55% | medium | Epoch AI | |
| Remote Labor Index | 1.7% | #12 of 14, top 86% | Epoch AI | ||
| DeepResearch Bench | 48.1% | high | Epoch AI | ||
| DeepResearch Bench | 49.6% | #8 of 24, top 34% | low | Epoch AI | |
| DeepResearch Bench | 48.6% | medium | Epoch AI | ||
| DeepResearch Bench | 48.9% | minimal | Epoch AI | ||
| BALROG | 32.8% | #14 of 35, top 40% | minimal | Epoch AI | |
| LMArena Search | 1133 | #29 of 32, top 91% | LMArena | 2026-08-24 | |
| METR Time Horizons | 69.4% | high | Epoch AI | ||
| METR Time Horizons | 69.6% | #10 of 32, top 32% | medium | Epoch AI |
Reasoning
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| ARC-AGI-2 | 9.9% | #49 of 83, top 60% | high | Epoch AI | |
| ARC-AGI-2 | 1.9% | low | Epoch AI | ||
| ARC-AGI-2 | 7.5% | medium | Epoch AI | ||
| ARC-AGI-2 | 0% | minimal | Epoch AI | ||
| SimpleBench | 56.7% | #31 of 77, top 41% | high | Epoch AI | |
| Kagi LLM Benchmark | 72.7% | #19 of 99, top 20% | Kagi LLM Benchmark | ||
| ARC-AGI-1 | 65.7% | #45 of 83, top 55% | high | Epoch AI | |
| ARC-AGI-1 | 44% | low | Epoch AI | ||
| ARC-AGI-1 | 56.2% | medium | Epoch AI | ||
| ARC-AGI-1 | 6% | minimal | Epoch AI | ||
| CritPt | 12.6% | #42 of 134, top 32% | high | Epoch AI | |
| CritPt | 0% | minimal | Epoch AI | ||
| Chess Puzzles | 37% | #27 of 129, top 21% | high | Epoch AI | 2025-12-08 |
| Chess Puzzles | 24% | low | Epoch AI | 2026-07-15 | |
| Chess Puzzles | 29% | medium | Epoch AI | 2026-07-15 | |
| Chess Puzzles | 16% | minimal | Epoch AI | 2026-07-15 | |
| EnigmaEval | 10.5% | #13 of 38, top 35% | Epoch AI | ||
| EBR-Bench | 12.7% | #18 of 24, top 75% | high | Epoch AI | 2026-06-29 |
| LMArena Hard Prompts | 1405 | LMArena | 2026-10-08 | ||
| LMArena Hard Prompts | 1416 | #110 of 297, top 38% | high | LMArena | 2026-10-08 |
| Mystery Game Puzzles | 23% | #35 of 74, top 48% | high | Epoch AI | 2026-08-05 |
| Mystery Game Puzzles | 16% | low | Epoch AI | 2026-08-27 | |
| Mystery Game Puzzles | 15% | medium | Epoch AI | 2026-08-27 | |
| Mystery Game Puzzles | 14% | minimal | Epoch AI | 2026-08-27 | |
| DTBench | 90.7% | #35 of 151, top 24% | high | Epoch AI | |
| LMCA | 40% | #45 of 125, top 36% | high | Epoch AI | |
| Epoch Capabilities Index | 150 | #53 of 213, top 25% | Epoch AI | 2025-08-07 | |
| ForecastBench | 61.4 | #10 of 72, top 14% | Epoch AI |
Math
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| FrontierMath (Tiers 1-3) | 55.4% | #43 of 81, top 54% | high | Epoch AI | 2026-06-10 |
| FrontierMath (Tiers 1-3) | 37.2% | low | Epoch AI | 2026-08-27 | |
| FrontierMath (Tiers 1-3) | 18.2% | minimal | Epoch AI | 2026-08-27 | |
| FrontierMath Tier 4 | 22% | #42 of 63, top 67% | high | Epoch AI | 2026-06-11 |
| OTIS Mock AIME 2024-2025 | 91.4% | #48 of 173, top 28% | high | Epoch AI | 2025-10-29 |
| OTIS Mock AIME 2024-2025 | 87.2% | medium | Epoch AI | 2025-08-07 | |
| OTIS Mock AIME 2024-2025 | 46.7% | minimal | Epoch AI | 2026-07-20 | |
| ProofBench | 18% | #51 of 77, top 67% | high | Epoch AI | |
| Omni-MATH | 64.7% | #7 of 57, top 13% | HELM Capabilities | ||
| LMArena Math | 1407 | #116 of 285, top 41% | LMArena | 2026-10-08 | |
| LMArena Math | 1399 | high | LMArena | 2026-10-08 | |
| MATH Level 5 | 98.1% | Best of 79 | high | Epoch AI | 2025-10-29 |
| MATH Level 5 | 97.9% | medium | Epoch AI | 2025-08-20 | |
| FrontierMath (Feb 2025 set) | 32.4% | #16 of 68, top 24% | high | Epoch AI | 2025-11-13 |
| FrontierMath (Feb 2025 set) | 27.2% | medium | Epoch AI | 2025-11-13 | |
| FrontierMath Tier 4 (v1) | 12.5% | #18 of 55, top 33% | high | Epoch AI | 2025-10-30 |
| FrontierMath Tier 4 (v1) | 6.3% | medium | Epoch AI | 2025-08-07 |
Knowledge
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| GPQA Diamond | 86.2% | #59 of 186, top 32% | high | Epoch AI | 2025-10-29 |
| GPQA Diamond | 85.4% | medium | Epoch AI | 2025-08-07 | |
| GPQA Diamond | 71.7% | minimal | Epoch AI | 2026-07-20 | |
| Humanity's Last Exam | 25.3% | #13 of 41, top 32% | Epoch AI | ||
| Humanity's Last Exam | 25.3% | high | Epoch AI | ||
| SimpleQA Verified | 50.1% | #25 of 77, top 33% | high | Epoch AI | 2026-08-27 |
| MMLU-Pro | 86.3% | #5 of 58, top 9% | HELM Capabilities | ||
| Confabulations (lower is better) | 10.3% | Best of 51 | medium reasoning | Lech Mazur benchmarks | |
| Vectara Hallucination Rate (lower is better) | 15.1% | Vectara Hallucination Leaderboard | |||
| Vectara Hallucination Rate (lower is better) | 14.7% | #86 of 96, top 90% | Vectara Hallucination Leaderboard | ||
| GPQA (HELM) | 79.2% | #2 of 57, top 4% | HELM Capabilities | ||
| LMArena Expert | 1404 | LMArena | 2026-10-08 | ||
| LMArena Expert | 1419 | #108 of 273, top 40% | high | LMArena | 2026-10-08 |
Multimodal
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Vision | 1232 | #66 of 122, top 55% | LMArena | 2026-10-09 | |
| LMArena Vision | 1208 | high | LMArena | 2026-10-09 | |
| GeoBench | 81% | #4 of 25, top 16% | medium | Epoch AI | |
| VPCT | 66% | #4 of 24, top 17% | high | Epoch AI | |
| VPCT | 63.2% | medium | Epoch AI |
Multilingual
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Non-English | 1394 | LMArena | 2026-10-08 | ||
| LMArena Non-English | 1397 | #110 of 297, top 38% | high | LMArena | 2026-10-08 |
| LMArena Chinese | 1422 | #125 of 285, top 44% | LMArena | 2026-10-08 | |
| LMArena Chinese | 1422 | high | LMArena | 2026-10-08 | |
| LMArena French | 1410 | #112 of 223, top 51% | LMArena | 2026-10-08 | |
| LMArena French | 1408 | high | LMArena | 2026-10-08 | |
| LMArena German | 1404 | LMArena | 2026-10-08 | ||
| LMArena German | 1416 | #82 of 231, top 36% | high | LMArena | 2026-10-08 |
| LMArena Japanese | 1409 | #51 of 211, top 25% | LMArena | 2026-10-08 | |
| LMArena Japanese | 1402 | high | LMArena | 2026-10-08 | |
| LMArena Korean | 1360 | #96 of 213, top 46% | LMArena | 2026-10-08 | |
| LMArena Korean | 1358 | high | LMArena | 2026-10-08 | |
| LMArena Russian | 1406 | #99 of 283, top 35% | LMArena | 2026-10-08 | |
| LMArena Russian | 1402 | high | LMArena | 2026-10-08 | |
| LMArena Spanish | 1399 | #112 of 226, top 50% | LMArena | 2026-10-08 | |
| LMArena Spanish | 1388 | high | LMArena | 2026-10-08 |
Instruction Following
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| IFEval | 87.5% | #15 of 57, top 27% | HELM Capabilities | ||
| LMArena Instruction Following | 1381 | LMArena | 2026-10-08 | ||
| LMArena Instruction Following | 1388 | #114 of 298, top 39% | high | LMArena | 2026-10-08 |
Long Context
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| Fiction.LiveBench | 97.2% | Best of 47 | medium | Epoch AI | |
| LMArena Longer Query | 1399 | #118 of 291, top 41% | LMArena | 2026-10-08 | |
| LMArena Longer Query | 1387 | high | LMArena | 2026-10-08 |
Writing & Preference
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Text | 1403 | LMArena | 2026-10-08 | ||
| LMArena Text | 1406 | #114 of 297, top 39% | high | LMArena | 2026-10-08 |
| LMArena Creative Writing | 1365 | #115 of 295, top 39% | LMArena | 2026-10-08 | |
| LMArena Creative Writing | 1364 | high | LMArena | 2026-10-08 | |
| Short-Story Creative Writing | 86% | Best of 39 | medium | Epoch AI | |
| EQ-Bench Creative Writing | 1627 | #39 of 115, top 34% | EQ-Bench | ||
| WildBench | 85.7% | #6 of 57, top 11% | HELM Capabilities | ||
| LMArena Multi-Turn | 1426 | #89 of 295, top 31% | LMArena | 2026-10-08 | |
| LMArena Multi-Turn | 1399 | high | LMArena | 2026-10-08 |
API pricing by provider
| Route | Input $/M | Output $/M | Cached input $/M | Checked |
|---|---|---|---|---|
| azure | $1.25 | $10 | $0.13 | 2026-10-10 |
| openai | $1.25 | $10 | $0.13 | 2026-10-10 |
| openrouter | $1.25 | $10 | $0.13 | 2026-10-10 |
Compare GPT-5
Other OpenAI models
- GPT-6 Astra70.8
- GPT-6.1 Sol65.6
- GPT-5.6 Sol65.0
- GPT-5.5 Pro64.3
- GPT-5.563.4
- GPT-6 Sol61.8
- GPT-5.459.4
- GPT-5.6 Terra59.2
Frequently asked questions
How good is GPT-5?
GPT-5 by OpenAI ranks 45th of 354 ranked models on the Noometry Index as of October 2026, with a score of 50.9. Its strongest category is long context, where it ranks 2nd. API pricing starts at $1.25 per million input tokens and $10 per million output tokens, with a 400K-token context window.
How much does GPT-5 cost?
GPT-5 costs $1.25 per million input tokens and $10 per million output tokens on OpenAI's own API, with cached input at $0.13.
What is GPT-5's context window?
GPT-5 accepts up to 400K tokens of input and can write up to 128K tokens in one response.
Is GPT-5 open source?
No. GPT-5 is proprietary and available only through OpenAI's API and partner platforms.
How fast is GPT-5?
GPT-5 generated about 2 output tokens per second in the Kagi LLM Benchmark's timed runs. Speed varies by provider, load and reasoning effort.
What are GPT-5's strengths and weaknesses?
Relative to other ranked models, GPT-5 places best in long context, multimodal, math and lowest in instruction following, multilingual, agentic & tool use.
What is GPT-5 best at?
Its best category is long context, where it ranks 2nd on Noometry.