OpenAI, released Jul 18, 2024
GPT-4o miniprice, context, benchmarks and release details
- Input, per 1M tokens
- $0.15models.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-mini
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Output, per 1M tokens
- $0.60models.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-mini
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
- Jul 18, 2024OpenAI API changelogPublished source fact
Retrieved Oct 9, 2026 · factual citation
Open source ↗
How the score breaks down
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, 05:13 UTC.
Around it on the leaderboard
- 138 Llama-3.2-1B 32.1
- 139 GPT-4.1 nano 32.1
- 140 GPT-4o 31.2
- 141 Llama 4 Maverick 17B Instruct 30.0
- 142 GPT-4o mini 22.9
Benchmark results
8 benchmarks, 8 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.
Open source ↗ 0.0
Open source ↗ 0.0
Open source ↗ 37.7
Open source ↗ 0.7
Open source ↗ 52.6
Open source ↗ 6.9
Open source ↗ 3.6
Open source ↗ 60.6
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, image, pdfmodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - First seen by SuperIndex
- Oct 8, 2026
- Coverage
- 80% of expected source weight
Reported (4)
- Aider polyglotOct 8, 2026
- ARC PrizeOct 8, 2026
- Epoch AI BenchmarkingOct 8, 2026
- LMArena / ArenaOct 8, 2026
Awaiting (2)
- Official model cards via models.dev5% of weight
- LiveBench15% of weight
Confidence rises as pending sources publish. Some sources never cover some models, so confidence reaches 100% at 80% of expected weight.