OpenAI, proprietary
GPT-5.4
GPT-5.4 by OpenAI ranks 16th of 354 ranked models on the Noometry Index as of October 2026, with a score of 59.4. Its strongest category is long context, where it ranks 8th. API pricing starts at $2.50 per million input tokens and $15 per million output tokens, with a 1.05M-token context window.
Last verified
Specifications
- Noometry rank
- #16 of 354
- Index score
- 59.4
- Evidence
- Confirmed 68 results
- Provider
- OpenAI
- Released
- March 5, 2026
- Weights
- Proprietary
- Reasoning
- Yes
- Context window
- 1.05M
- Max output
- 128K
- Input price
- $2.50 / M
- Output price
- $15 / M
- Blended price
- $5.63 / M
- Output speed
- 12 tokens/s Kagi
- Value
- #183 of 219
- Knowledge cutoff
- August 2025
- Input
- text, image, pdf
Category scores
Each category score combines every public result we have in that category.
- Coding 52.6
- Agentic & Tool Use 46.5
- Reasoning 61.8
- Math 73.5
- Knowledge 65.3
- Multimodal 43.7
- Multilingual 56.2
- Instruction Following 77.1
- Long Context 50.3
- Writing & Preference 71.9
| Category | Score | Rank | Results |
|---|---|---|---|
| Coding | 52.6 | #33 | 8 |
| Agentic & Tool Use | 46.5 | #13 | 6 |
| Reasoning | 61.8 | #19 | 13 |
| Math | 73.5 | #19 | 6 |
| Knowledge | 65.3 | #14 | 5 |
| Multimodal | 43.7 | #20 | 3 |
| Multilingual | 56.2 | #23 | 1 |
| Instruction Following | 77.1 | #27 | 1 |
| Long Context | 50.3 | #8 | 3 |
| Writing & Preference | 71.9 | #17 | 5 |
Strengths and weaknesses
Categories where GPT-5.4 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 | 50.3 | +9.4 | #8 of 296, top 3% |
| Knowledge | 65.3 | +28.0 | #14 of 314, top 5% |
| Reasoning | 61.8 | +38.2 | #19 of 350, top 6% |
Weakest categories
| Category | Score | vs median | Rank |
|---|---|---|---|
| Multimodal | 43.7 | +5.1 | #20 of 128, top 16% |
| Coding | 52.6 | +13.9 | #33 of 340, top 10% |
| Instruction Following | 77.1 | +5.9 | #27 of 305, top 9% |
Closest competitors
The models ranked just above and below GPT-5.4. When scores are this close, price and speed are often the better way to choose.
| Model | Rank | Score | Blended $/M | Speed | |
|---|---|---|---|---|---|
| GPT-6 Sol | #12 | 61.8 | $4 | — | Compare |
| Claude Opus 4.8 | #13 | 60.7 | $10 | 34 | Compare |
| Gemini 3.7 Flash | #14 | 59.8 | $1.50 | — | Compare |
| Kimi K3 | #15 | 59.5 | $6 | — | Compare |
| GPT-5.6 Terra | #17 | 59.2 | $4.50 | 11 | Compare |
| GPT-5.4 Pro | #18 | 58.9 | $67.50 | — | Compare |
| Claude Opus 4.7 | #19 | 58.3 | $10 | 33 | Compare |
| Claude Opus 4.6 | #20 | 58.2 | $10 | 19 | Compare |
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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 | 76.9% | #8 of 32, top 25% | high | Epoch AI | 2026-03-06 |
| DeepSWE | 51.8% | #23 of 29, top 80% | xhigh | Epoch AI | |
| LMArena WebDev | 1465 | #54 of 113, top 48% | LMArena | 2026-10-08 | |
| LMArena WebDev | 1400 | LMArena | 2026-10-08 | ||
| LMArena WebDev | 1444 | LMArena | 2026-10-08 | ||
| SciCode | 56.6% | #18 of 121, top 15% | xhigh | Epoch AI | |
| GSO | 25.5% | high | Epoch AI | ||
| GSO | 31.4% | #10 of 31, top 33% | xhigh | Epoch AI | |
| WeirdML | 57.4% | none | Epoch AI | ||
| WeirdML | 77.7% | #13 of 119, top 11% | xhigh | Epoch AI | |
| LMArena Coding | 1497 | #24 of 294, top 9% | high | LMArena | 2026-10-08 |
| MirrorCode | 15.6% | #7 of 9, top 78% | high | Epoch AI | 2026-08-10 |
| ALE-Bench | 1,607 | #13 of 105, top 13% | high | Epoch AI | |
| ALE-Bench | 1,521 | medium | Epoch AI | ||
| ALE-Bench | 1,086 | none | Epoch AI | ||
| AlgoTune | 1.85 | #3 of 18, top 17% | high | Epoch AI |
Agentic & Tool Use
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| Terminal-Bench | 81.8% | #2 of 41, top 5% | Epoch AI | ||
| APEX-Agents | 52.4% | #23 of 49, top 47% | Epoch AI | ||
| τ²-bench Banking | 39.4% | #10 of 26, top 39% | xhigh | τ²-bench | 2026-03-25 |
| DeepResearch Bench | 35.1% | #24 of 24, top 100% | low | Epoch AI | |
| PostTrainBench | 19% | #11 of 11, top 100% | high | Epoch AI | |
| GBAEval | 45.1% | #10 of 23, top 44% | Epoch AI | ||
| LMArena Search | 1197 | #16 of 32, top 50% | LMArena | 2026-08-24 | |
| METR Time Horizons | 74.3% | #7 of 32, top 22% | xhigh | Epoch AI | |
| Vending-Bench 2 | 6,144 | #19 of 60, top 32% | Epoch AI |
Reasoning
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| ARC-AGI-2 | 67.5% | high | Epoch AI | ||
| ARC-AGI-2 | 29.2% | low | Epoch AI | ||
| ARC-AGI-2 | 55.4% | medium | Epoch AI | ||
| ARC-AGI-2 | 74% | #18 of 83, top 22% | xhigh | Epoch AI | |
| Kagi LLM Benchmark | 63.8% | #34 of 99, top 35% | Kagi LLM Benchmark | ||
| NYT Connections (extended) | 91.3% | #15 of 91, top 17% | xhigh reasoning | Lech Mazur benchmarks | |
| ARC-AGI-1 | 92.7% | high | Epoch AI | ||
| ARC-AGI-1 | 68.2% | low | Epoch AI | ||
| ARC-AGI-1 | 86.2% | medium | Epoch AI | ||
| ARC-AGI-1 | 93.7% | #19 of 83, top 23% | xhigh | Epoch AI | |
| CritPt | 23.4% | #18 of 134, top 14% | xhigh | Epoch AI | |
| Chess Puzzles | 38% | high | Epoch AI | 2026-07-15 | |
| Chess Puzzles | 20% | low | Epoch AI | 2026-07-15 | |
| Chess Puzzles | 38% | medium | Epoch AI | 2026-07-15 | |
| Chess Puzzles | 5% | none | Epoch AI | 2026-07-15 | |
| Chess Puzzles | 44% | #15 of 129, top 12% | xhigh | Epoch AI | 2026-03-11 |
| EnigmaEval | 16% | #9 of 38, top 24% | xhigh | Epoch AI | |
| Thematic Generalization | 80% | #2 of 23, top 9% | xhigh reasoning | Lech Mazur benchmarks | |
| EBR-Bench | 25.4% | #12 of 24, top 50% | xhigh | Epoch AI | 2026-06-25 |
| LMArena Hard Prompts | 1485 | #24 of 297, top 9% | high | LMArena | 2026-10-08 |
| Mystery Game Puzzles | 17% | low | Epoch AI | 2026-08-27 | |
| Mystery Game Puzzles | 28% | medium | Epoch AI | 2026-08-28 | |
| Mystery Game Puzzles | 16% | none | Epoch AI | 2026-08-30 | |
| Mystery Game Puzzles | 37% | #16 of 74, top 22% | xhigh | Epoch AI | 2026-07-24 |
| DTBench | 94.4% | #22 of 151, top 15% | xhigh | Epoch AI | |
| LMCA | 52% | #19 of 125, top 16% | xhigh | Epoch AI | |
| Epoch Capabilities Index | 156.81 | #17 of 213, top 8% | Epoch AI | 2026-03-05 | |
| ForecastBench | 59.5 | #38 of 72, top 53% | Epoch AI |
Math
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| FrontierMath (Tiers 1-3) | 78.6% | #17 of 81, top 21% | xhigh | Epoch AI | 2026-06-11 |
| FrontierMath Tier 4 | 49% | #18 of 63, top 29% | xhigh | Epoch AI | 2026-06-11 |
| MathArena Final-Answer Competitions | 83.1% | #5 of 29, top 18% | xhigh | MathArena | |
| OTIS Mock AIME 2024-2025 | 97.8% | #25 of 173, top 15% | high | Epoch AI | 2026-07-15 |
| OTIS Mock AIME 2024-2025 | 84.4% | low | Epoch AI | 2026-07-15 | |
| OTIS Mock AIME 2024-2025 | 95.6% | medium | Epoch AI | 2026-07-15 | |
| OTIS Mock AIME 2024-2025 | 57.8% | none | Epoch AI | 2026-07-15 | |
| OTIS Mock AIME 2024-2025 | 95.3% | xhigh | Epoch AI | 2026-03-06 | |
| ProofBench | 56% | #24 of 77, top 32% | xhigh | Epoch AI | |
| LMArena Math | 1488 | #21 of 285, top 8% | high | LMArena | 2026-10-08 |
| FrontierMath (Feb 2025 set) | 47.6% | #4 of 68, top 6% | xhigh | Epoch AI | 2026-03-06 |
| FrontierMath Tier 4 (v1) | 27.1% | #7 of 55, top 13% | xhigh | Epoch AI | 2026-03-06 |
Knowledge
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| GPQA Diamond | 89.9% | high | Epoch AI | 2026-07-15 | |
| GPQA Diamond | 84.8% | low | Epoch AI | 2026-07-15 | |
| GPQA Diamond | 88.9% | medium | Epoch AI | 2026-07-15 | |
| GPQA Diamond | 74.7% | none | Epoch AI | 2026-07-15 | |
| GPQA Diamond | 93.3% | #17 of 186, top 10% | xhigh | Epoch AI | 2026-03-06 |
| Humanity's Last Exam | 36.2% | #8 of 41, top 20% | xhigh | Epoch AI | |
| SimpleQA Verified | 45.1% | #36 of 77, top 47% | xhigh | Epoch AI | 2026-08-27 |
| Vectara Hallucination Rate (lower is better) | 7% | #29 of 96, top 31% | Vectara Hallucination Leaderboard | ||
| LMArena Expert | 1507 | #19 of 273, top 7% | high | LMArena | 2026-10-08 |
Multimodal
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Vision | 1303 | #15 of 122, top 13% | high | LMArena | 2026-10-09 |
| Blueprint-Bench 2 | 27.1% | #19 of 31, top 62% | Epoch AI | ||
| Furniture Assembly | 37.5% | #17 of 31, top 55% | xhigh | Epoch AI | 2026-09-10 |
| LMArena Document | 1471 | #11 of 38, top 29% | LMArena | 2026-09-13 |
Multilingual
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Non-English | 1465 | #23 of 297, top 8% | high | LMArena | 2026-10-08 |
| LMArena Chinese | 1519 | #28 of 285, top 10% | high | LMArena | 2026-10-08 |
| LMArena French | 1493 | #17 of 223, top 8% | high | LMArena | 2026-10-08 |
| LMArena German | 1472 | #23 of 231, top 10% | high | LMArena | 2026-10-08 |
| LMArena Japanese | 1485 | #13 of 211, top 7% | high | LMArena | 2026-10-08 |
| LMArena Korean | 1448 | #19 of 213, top 9% | high | LMArena | 2026-10-08 |
| LMArena Russian | 1480 | #21 of 283, top 8% | high | LMArena | 2026-10-08 |
| LMArena Spanish | 1454 | #46 of 226, top 21% | high | LMArena | 2026-10-08 |
Instruction Following
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Instruction Following | 1469 | #24 of 298, top 9% | high | LMArena | 2026-10-08 |
Long Context
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| CL-bench | 27.9% | Best of 19 | xhigh | Epoch AI | |
| CL-bench Life | 13.8% | Epoch AI | |||
| CL-bench Life | 19.3% | high | Epoch AI | ||
| CL-bench Life | 21.7% | #2 of 13, top 16% | xhigh | Epoch AI | |
| LMArena Longer Query | 1473 | #32 of 291, top 11% | high | LMArena | 2026-10-08 |
Writing & Preference
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Text | 1469 | #28 of 297, top 10% | high | LMArena | 2026-10-08 |
| LMArena Creative Writing | 1439 | #40 of 295, top 14% | high | LMArena | 2026-10-08 |
| EQ-Bench Creative Writing | 1840 | #20 of 115, top 18% | EQ-Bench | ||
| EQ-Bench 4 | 1272 | #7 of 28, top 25% | EQ-Bench | ||
| LMArena Multi-Turn | 1482 | #17 of 295, top 6% | high | LMArena | 2026-10-08 |
API pricing by provider
| Route | Input $/M | Output $/M | Cached input $/M | Checked |
|---|---|---|---|---|
| azure | $2.50 | $15 | $0.25 | 2026-10-10 |
| bedrock | $2.75 | $16.50 | $0.28 | 2026-10-10 |
| openai | $2.50 | $15 | $0.25 | 2026-10-10 |
| openrouter | $2.50 | $15 | $0.25 | 2026-10-10 |
Compare GPT-5.4
- GPT-5.4 vs GPT-5.2
- GPT-5.4 vs Kimi K3
- GPT-5.4 vs GPT-5.6 Terra
- GPT-5.4 vs Gemini 3.7 Flash
- GPT-5.4 vs GPT-5.4 Pro
- GPT-5.4 vs Claude Opus 4.8
- GPT-5.4 vs Claude Opus 4.7
- GPT-5.4 vs Claude Fable 5.1
- GPT-5.4 vs Gemini 3.8 Flash
- GPT-5.4 vs Grok 4.6
- GPT-5.4 vs Qwen3.8 Max
- GPT-5.4 vs GLM-5.3
- GPT-5.4 vs Muse Spark 1.3
- GPT-5.4 vs DeepSeek V4 Pro
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-5.6 Terra59.2
- GPT-5.4 Pro58.9
Frequently asked questions
How good is GPT-5.4?
GPT-5.4 by OpenAI ranks 16th of 354 ranked models on the Noometry Index as of October 2026, with a score of 59.4. Its strongest category is long context, where it ranks 8th. API pricing starts at $2.50 per million input tokens and $15 per million output tokens, with a 1.05M-token context window.
How much does GPT-5.4 cost?
GPT-5.4 costs $2.50 per million input tokens and $15 per million output tokens on OpenAI's own API, with cached input at $0.25.
What is GPT-5.4's context window?
GPT-5.4 accepts up to 1.05M tokens of input and can write up to 128K tokens in one response.
Is GPT-5.4 open source?
No. GPT-5.4 is proprietary and available only through OpenAI's API and partner platforms.
How fast is GPT-5.4?
GPT-5.4 generated about 12 output tokens per second in the Kagi LLM Benchmark's timed runs. Speed varies by provider, load and reasoning effort.
What are GPT-5.4's strengths and weaknesses?
Relative to other ranked models, GPT-5.4 places best in long context, knowledge, reasoning and lowest in multimodal, coding, instruction following.
What is GPT-5.4 best at?
Its best category is long context, where it ranks 8th on Noometry.