[whatmodel.sh](../../README.md) / GPT-4 (0613)
# GPT-4 (0613)
OpenAI · released 2023-06 · proprietary
**score 52.7** ±0.5 · #323 of 732 · from 29 benchmark results across 17 sources
Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only.
## What it's good at
● marks GPT-4 (0613) among every model on that task or test, worst to best.
task vs the others rank counts tests
coding ▁▁▁▃▅▇●▇▅▄▃▁ #228 of 469 23% 6
chat & writing ▁▁▁▃▆▄●█▆▇▇▃ #269 of 402 28% 6
math ▁▁▃●█▆▄█▄▂▁▁ #337 of 431 9.0% 3
coding · #228 of 469 · 23% of its score
Beats [Qwen3.5 4B](qwen3-5-4b.md), [Qwen3-VL 32B Instruct](qwen3-vl-32b-instruct.md), [Solar Open 100B (102B-A12B)](solar-open-100b.md) here, though they rank higher overall. Trails [QwQ-32B-Preview](qwq-32b-preview.md), [Ministral 3 3B Reasoning 2512](ministral-3-3b-reasoning.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
HumanEval 82.3% ▁█▄▅▇█·▄▇▅▄● beats 41/42 easy · avg 75% 8.5% sharp
LiveCodeBench official (Jan 1–Nov… 32.5% ▁▁·▁▂▄▆●▅▂·▂ beats 17/31 hard · avg 23% 6.3% sharp · at its level
Aider code editing (133 Exercism … 67.7% ▁·▁▂▄▁▆▄●▆▂▂ beats 44/62 medium · avg 51% 5.6% sharp · at its level
CRUXEval-I 69.8% ▁··▁▅▂█▇▁··● beats 22/22 medium · avg 52% 1.1% at its level
CRUXEval-O 68.7% ▁·▂▃▁█▁▂···● beats 22/22 medium · avg 51% 1.0% blunt · at its level
Tulu 2: CodexEval pass@10 87.0% ▃▃▃·▆▃▃█▃▂▂● beats 23/25 easy · avg 83% 0.9% sharp
chat & writing · #269 of 402 · 28% of its score
Beats [Ministral 3 14B Reasoning 2512](ministral-3-14b-reasoning.md), [Ministral 3 14B](ministral-3-14b.md), [OpenThinker2 32B](openthinker2-32b.md) here, though they rank higher overall. Trails [Flan-T5 XXL](flan-t5-xxl.md), [North Micro Vision Instruct (2.4B)](north-micro-vision-instruct.md), [Granite 4.0 H 1B](granite-4-0-h-1b.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
AlpacaEval 2 length-controlled 30.2% ▁▂▂▃▆▆█●▄▄▁▁ beats 78/122 medium · avg 35% 13% sharp · at its level
Arena-Hard (v0.1, GPT-4-1106 judg… 37.9% ▂▁▁▅█▅●▃▃▅▃▁ beats 33/60 medium · avg 47% 7.2% sharp · at its level
LMArena (text) 1276.3 ▁▁▁▂▃▃●▆▆▇█▃ beats 106/385 avg 1260 3.0% blunt
Polyrating rating (bias-aware re-… 1191.0 ▂▁▂▁▃▇█▆▇●▂▂ beats 80/95 avg 1187 2.7% typical
MT-Bench (GPT-4 single-answer gra… 9.1800 MT-Bench score (1-10) ▆▂▂▆▆▄██▂▄▄● beats 27/28 avg 8.539 MT-Bench scor… 2.1% sharp · noisy
AlpacaEval 1.0 win rate (vs text-… 93.8% ▂▂·▆·▇▃▆█●▄▂ beats 38/45 very easy · avg 94% 0.2% sharp · maxed out · noisy
math · #337 of 431 · 9.0% of its score
Trails [Gemma 2B (base)](gemma-2b-base.md), [Stable Code 3B](stable-code-3b.md), [Zephyr 7B beta](zephyr-7b-beta.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
MATH level 5 23.0% ▂▂▅●▄█▆▃▅▂▃▄ beats 21/92 hard · avg 28% 6.4% sharp · at its level
GSM8K 95.0% ▆▂▅█▅▅▃▆···● beats 25/25 easy · avg 72% 1.5% sharp
OTIS mock AIME 2024–2025 1.1% ●▃▄▃▃▃▇▇█▃▂▅ beats 8/197 very hard · avg 7.2% 1.1% sharp · noisy
other tests (14)
test result vs the others in its run difficulty counts why
LiveBench 2024-07-26 45.6% ▁▁▁▂▂▃▂█▆●▅▃ beats 48/61 medium · avg 38% 12% at its level
EvoEval (overall) 66.2% ▂▂▃▄▄█▁▄▅▃▁● beats 42/42 medium · avg 52% 8.2% at its level
GPQA Diamond 30.7% ▁▁▁▁●▄▆▄▅▇█▅ beats 18/211 hard · avg 39% 3.8% sharp
BigCodeBench (Instruct) 45.9% ▃▂·▆▆██▆▅▃●▃ beats 31/33 medium · avg 39% 3.6% at its level
BIG-Bench Hard 89.1% ▁·····▂█▂▅·● beats 25/25 easy · avg 74% 3.5% sharp · at its level
BigCodeBench (Complete) 48.4% ▂▁▁▄▂▅▇█●▂▂▂ beats 47/58 medium · avg 48% 3.3% at its level
MMLU 81.4% ▁▁▃▃▄█▄▁█··● beats 25/25 medium · avg 73% 1.6% at its level
EQ-Bench v1 (60 questions, paper … 62.5% ▂··▄·▂▆▄▂█·● beats 14/14 medium · avg 53% 1.3% at its level
API-Bank evaluation system, zero-… 60.2% ▄······█··▄● beats 4/4 medium · avg 50% 0.9% at its level
Tulu 2: TyDiQA gold passage, 1-sh… 65.2% ▂··▁▃▂▂▂█▅▁● beats 25/25 medium · avg 59% 0.4% blunt · at its level
FANToM BeliefQ [Choice], short co… 73.3% █·····▂····● beats 11/11 very hard · avg 55% 0.3% sharp · noisy
Chess Puzzles (Epoch) 4.0% ●▁▁▁▁▂▃▃▃▂▁▁ beats 13/137 very hard · avg 5.8% 0.2% sharp · too hard for it · noisy
Vectara hallucination leaderboard… 98.2% ▁▁▂▃▄▄█▆▃●▂▁ beats 125/140 very easy · avg 94% 0.2% blunt · maxed out · noisy
Mystery Game Puzzles (Epoch) 12.0% █··●▃▇▄█▂▄▂▁ beats 17/77 very hard · avg 9.4% 0.1% sharp · too hard for it · noisy
source results share of the score
Top Leaderboard Ranking = Top Coding Pr… 2 17% ▇▇
AlpacaEval 1.0 and 2.0 leaderboards 2 13% ▇▇
LiveBench model judgments 1 12% ▇
Epoch AI 5 11% ▇
Tulu 2 5 8% ▇
Arena-Hard-Auto v0.1 leaderboard 1 7% ▇
BigCodeBench paper 2 7% ▇
LiveCodeBench official website results 1 6% ▇
Aider code editing benchmark runs 1 6% ▇
LMArena leaderboard dataset 1 3% ▇
Polyrating: A Cost-Effective and Bias-A… 1 3% ▇
CRUXEval published evaluation results 2 2% ▇
LMSYS Chatbot Arena leaderboard Space: … 1 2% ▇
EQ-Bench: An Emotional Intelligence Ben… 1 1% ▇
API-Bank: A Comprehensive Benchmark for… 1 1% ▇
FANToM: A Benchmark for Stress-testing … 1 0% ▇
Vectara hallucination leaderboard 1 0% ▇
prior: pull toward the middle 0% ▇
weighted average = 52.7
Licences: Top Leaderboard Ranking = Top Coding Proficiency ([CC BY 4.0](../../licenses/paper-2403.19114v1-CC-BY-4.0.txt)) · AlpacaEval 1.0 and 2.0 leaderboards ([Apache-2.0](https://www.apache.org/licenses/LICENSE-2.0)) · LiveBench model judgments ([Apache-2.0 (stated in the LiveBench datasheet)](https://www.apache.org/licenses/LICENSE-2.0)) · Epoch AI ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · Tulu 2 ([CC BY 4.0](../../licenses/CC-BY-4.0.txt)) · Arena-Hard-Auto v0.1 leaderboard ([Apache-2.0](../../licenses/arena-hard-auto-v0-1-Apache-2.0.txt)) · BigCodeBench paper ([CC BY 4.0](http://creativecommons.org/licenses/by/4.0/)) · LiveCodeBench official website results ([CC-BY-SA-4.0](../../licenses/lcb-sharealike-NOTICE.txt)) · Aider code editing benchmark runs ([Apache-2.0](../../licenses/aider-polyglot-runs-Apache-2.0.txt)) · LMArena leaderboard dataset ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · Polyrating: A Cost-Effective and Bias-Aware Rating System for LLM Evaluation ([CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/)) · CRUXEval published evaluation results ([MIT](../../licenses/cruxeval-published-results-MIT.txt)) · LMSYS Chatbot Arena leaderboard Space: MT-Bench column of the published leaderboard table ([Apache-2.0](https://www.apache.org/licenses/LICENSE-2.0)) · EQ-Bench: An Emotional Intelligence Benchmark for Large Language Models ([CC BY 4.0](../../licenses/paper-2312.06281v2-CC-BY-4.0.txt)) · API-Bank: A Comprehensive Benchmark for Tool-Augmented LLMs ([CC BY 4.0](../../licenses/acl-2023-emnlp-main-187-CC-BY-4-0.txt)) · FANToM: A Benchmark for Stress-testing Machine Theory of Mind in Interactions ([CC BY 4.0](../../licenses/acl-2023-emnlp-main-890-CC-BY-4-0.txt)) · Vectara hallucination leaderboard ([Apache-2.0](https://www.apache.org/licenses/LICENSE-2.0))
## How to run it
### Through an API
api (OpenAI) · $37.50/M blended · $30 in / $60 out per 1M tokens · [developers.openai.com](https://developers.openai.com/api/docs/models/gpt-4)
[price source](https://developers.openai.com/api/docs/models/gpt-4): USD per 1M tokens, OpenAI API standard processing, model page 'gpt-4' whose default snapshot is gpt-4-0613: input $30, output $60; cached-input, Batch and other tiers excluded. Currency: USD. OpenAI official model page, observed 2026-09-28. · [context source](https://developers.openai.com/api/docs/models/gpt-4): OpenAI model page for gpt-4 (default snapshot gpt-4-0613): 8,192 context window. Observed 2026-09-28.
[interactive version](https://whatmodel.sh/model/gpt-4-0613) · [JSON](https://whatmodel.sh/api?format=json&all=1)