GPT-4 (0613): benchmark scores, price and ranking
GPT-4 (0613) from OpenAI ranks #164 of 743 LLMs on the LLMs Tiger aggregate benchmark score (50.8), based on 2 benchmark results captured up to 2026-10-13.
- Organisation
- OpenAI
- Type
- Frontier model
- Open weights
- No
- Released
- 2023-06-13 (source: name)
- Context window
- 8,192 tokens
- Cheapest API price
- $30.00 in / $60.00 out per million tokens (via azure, observed 2026-10-13T20:47Z)
- Aggregate rank
- #164 of 743 (score 50.8)
Across the 2 benchmarks where at least ten models are scored, GPT-4 (0613) is in the top 10% on 0 and in the top half on 1.
Its cheapest listed input price, $30.00 per million tokens, is lower than that of 1% of the 427 models with a listed price.
GPT-4 (0613) benchmark results
| Benchmark | Score | Rank | Source | Captured |
|---|---|---|---|---|
| Aider Code Editing | 67.7% | #19 of 92 | Aider Aider Code Editing leaderboard | 2026-10-13 |
| SWE-bench Lite | 23.7% | #12 of 20 | SWE-bench Lite leaderboard | 2026-10-13 |
About GPT-4 (0613)
GPT-4 (0613) is a frontier model from OpenAI. It was released on 2023-06-13, according to the model's own name. It accepts up to 8,192 tokens of input at once. The cheapest API listing we track charges $30.00 per million input tokens and $60.00 per million output tokens, through azure. We hold 2 benchmark results for it across 1 area, and none is in the top tenth of its board.
Where GPT-4 (0613) stands
On our aggregate score, GPT-4 (0613) is #164 of 743 ranked models, in the top quarter. Its score is 50.8; the scale is centred on 50, so it sits 0.8 points above the typical model. That beats 78% of the ranked field. Among the 88 ranked OpenAI models it is #21. The next one up is GPT-5.6 Luna 2026-07-30 (Max) at 50.9. The next one down is gpt-4-0314 at 50.8.
GPT-4 (0613), benchmark by benchmark
Aider Code Editing puts GPT-4 (0613) at 67.7%, #19 of 92. That beats 79% of the models tested, but 16.5 points short of Claude 3.5-Sonnet-20241022 (84.2%). The results either side are claude-3-opus-20240229 (68.4%) and Dracarys2-72B-Instruct (66.9%). It covers Aider official benchmark. The board median is 55.6%, so GPT-4 (0613) is 12.1 points above it. Source: Aider Aider Code Editing leaderboard, captured 2026-10-13.
GPT-4 (0613) lands below the middle on SWE-bench Lite: 23.7%, #12 of 20, with 55% of the field scoring higher. Claude 4 Sonnet leads at 56.7%; the closest result above is Qwen2.5 (7B + 72B) at 24.7%. It covers real GitHub issues resolved. The board median is 24.7%, so GPT-4 (0613) is 1.0 points below it. Source: SWE-bench Lite leaderboard, captured 2026-10-13.
Strengths and weaknesses
Software engineering: solid, ahead of 60% of the field on average across 2 benchmarks. Its best board here is Aider Code Editing (#19 of 92) and its weakest is SWE-bench Lite (#12 of 20).
Price and value
The median input price across the 427 priced models is $0.500 per million tokens, so GPT-4 (0613) costs more than the typical listing. Models that score within 1.5 points or better and cost less: Qwen2.5-Coder-7B-Instruct ($0.010, 49.5), DeepSeek V4 Flash 0731 (max) ($0.016, 53.1), GLM-5.3-Flash (max) ($0.026, 49.6). Similar scores cost more on gpt-4.5-preview ($75.00).
Release history
The OpenAI model released before it was GPT-4 (Mar 2023) on 2023-03-14, which scores 43.7. The next one was GPT-4 (Jun 2023) on 2023-06-13, at 41.2.
Reading these numbers
The 2 scores on this page come from 2 sources: Aider Aider Code Editing leaderboard (1), SWE-bench Lite leaderboard (1). 1 of them come from an official leaderboard and 1 from datasets or third-party runs. With 2 results the aggregate rank can move a lot when one new score arrives.
Models ranked nearby
- #161 Optimus Alpha (50.9)
- #162 DeepSeek-V2.5 (50.9)
- #163 Qwen3.8 Max (0902) (xhigh) (50.8)
- #165 Claude Code + GLM-5.3 (50.8)
- #166 gpt-4-0314 (50.8)
- #167 SWE-1.7 (50.8)
More from OpenAI
- GPT-6 Astra (max) (#2, 64.0)
- GPT-6.1 Sol (max) (#5, 60.6)
- GPT-5.6 Sol (max) (#6, 60.1)
- GPT-6 Sol (max) (#7, 60.0)
- GPT-5.5 (xhigh) (#11, 58.0)
- GPT-5.6 Terra (max) (#12, 57.8)
Compare it on the live leaderboard → · How the aggregate score works