OpenAI, released Aug 6, 2024
GPT-4o (2024-08-06)price, context, benchmarks and release details
Provisional: not enough results to rank yet 100% confidence 100 percent, Full confidence, 4 of 5 expected sources in
36.7
SI Score
#133 of 142 ranked models
- Input, per 1M tokens
- $2.50models.devFirst-party hosted API; MIT models.dev transcription. Provider documentation: https://platform.openai.com/docs/models. Exact canonical endpoint; lowest short-context Standard USD token tier; cache/batch discounts excluded. Deprecated endpoints excluded; openai/gpt-4o-2024-08-06
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Output, per 1M tokens
- $10.00models.devFirst-party hosted API; MIT models.dev transcription. Provider documentation: https://platform.openai.com/docs/models. Exact canonical endpoint; lowest short-context Standard USD token tier; cache/batch discounts excluded. Deprecated endpoints excluded; openai/gpt-4o-2024-08-06
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Context window
- 128Kmodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Max output
- 16.4Kmodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Released
- Aug 6, 2024models.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗
How the score breaks down
Coding (weight 40 percent) 17.0
Math (weight 15 percent) 22.7
Preference (weight 15 percent) 60.2
Reasoning (weight 30 percent) 49.2
Weights: reasoning 30%, math 15%, coding 40%, preference 15%. Results use fixed 0–100 scales before averaging, and thin evidence is pulled toward 50. Method si-v3-retained-evidence-2, computed Oct 9, 2026, 06:15 UTC.
Around it on the leaderboard
- 131 Nova Pro 37.4
- 132 GPT-4.1 mini 36.9
- 133 GPT-4o (2024-08-06) 36.7
- 134 Nova Lite 36.6
- 135 Mistral Large 2.1 35.3
Benchmark results
7 benchmarks, 7 resultsEach row shows the best published result. Where a model was tested at several settings, such as reasoning effort, open the row to see each one. Hover or tap a value for its source.
GPQA Diamondreasoning 49.2%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Jan 27, 2025
Retrieved Oct 9, 2026 · CC-BY
Open source ↗ 49.2
Open source ↗ 49.2
FrontierMath Tiers 1–3 (v2)math 0.4%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Aug 27, 2026
Retrieved Oct 9, 2026 · CC-BY
Open source ↗ 0.4
Open source ↗ 0.4
MATH Level 5math 53.3%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Jan 27, 2025
Retrieved Oct 9, 2026 · CC-BY
Open source ↗ 53.3
Open source ↗ 53.3
OTIS Mock AIME 2024–2025math 6.4%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Feb 25, 2025
Retrieved Oct 9, 2026 · CC-BY
Open source ↗ 6.4
Open source ↗ 6.4
Aider Polyglotcoding 23.1%Aider polyglotPublished source fact [variant] Aider polyglot; 225 cases; 2 attemptsPublished Dec 30, 2024
Retrieved Oct 9, 2026 · Apache-2.0
Open source ↗ 23.1
Open source ↗ 23.1
Terminal-Benchcoding 8.3%Official model cards via models.devLab-reported; metric success rate; transcribed by MIT models.dev catalog; not independently evaluated [variant] Published Mar 11, 2026
Retrieved Oct 9, 2026 · factual citation; MIT transcription
Open source ↗ 8.3
Open source ↗ 8.3
LMArena Textpreference 1282.5 eloLMArena / ArenaPublished source fact [variant] text / overallPublished Oct 8, 2026
Retrieved Oct 9, 2026 · CC-BY-4.0
Open source ↗ 60.2
Open source ↗ 60.2
Normalization uses a fixed 0–100 scale for each unit, independent of other models. Compare evaluation conditions before reading a small gap as decisive. “Lab-reported” marks the provider's own published figure.
Details and sources
- Open weights
- Nomodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - License
- not yet reported
- Input modalities
- text, imagemodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - First seen by SuperIndex
- Oct 8, 2026
- Coverage
- 83% of expected source weight
Reported (4)
- Aider polyglotOct 8, 2026
- Epoch AI BenchmarkingOct 8, 2026
- Official model cards via models.devOct 8, 2026
- LMArena / ArenaOct 8, 2026
Awaiting (1)
- LiveBench17% of weight
Confidence rises as pending sources publish. Some sources never cover some models, so confidence reaches 100% at 80% of expected weight.