GPT-4o (2024-11-20): Price, Context, Benchmarks, and Release Details
42.2
SI Score (method si-v3-retained-evidence-2)
#119 of 140 ranked
61% confidence 61 percent, Medium confidence — 3 of 5 expected sources in
Coverage 49% of expected source weight · 100% confidence at 80% coverage
Pillar breakdown
Coding (weight 40 percent) 23.2
Math (weight 15 percent) 35.3
Preference (weight 15 percent) —
Reasoning (weight 30 percent) 47.9
Pillar weights: reasoning 30% · math 15% · coding 40% · preference 15%. Benchmark results use fixed 0–100 scales before averaging; incomplete evidence is shrunk toward 50.
Facts
- Input price / 1M
- $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-2024-11-20
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Output price / 1M
- $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-2024-11-20
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
- Nov 20, 2024models.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - 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 ↗
Benchmark results
6 results| Benchmark | Raw result | Normalized (0–100) | Pillar |
|---|---|---|---|
| aider polyglot | 18.2%Aider polyglotPublished source fact [variant] Aider polyglot; 225 cases; 2 attemptsPublished Dec 30, 2024
Retrieved Oct 9, 2026 · Apache-2.0 Open source ↗ | 18.2 | coding |
| gpqa diamond | 47.9%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Feb 5, 2025
Retrieved Oct 9, 2026 · CC-BY Open source ↗ | 47.9 | reasoning |
| math level 5 | 49.8%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Feb 5, 2025
Retrieved Oct 9, 2026 · CC-BY Open source ↗ | 49.8 | math |
| otis mock aime 2024 2025 | 6.3%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 ↗ | 6.3 | math |
| swe bench verified | 31.0%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Feb 11, 2026
Retrieved Oct 9, 2026 · CC-BY Open source ↗ | 31.0 | coding |
| terminal bench | 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 | coding |
Normalization uses fixed absolute 0–100 scales for each unit, independently of other models that have a result on each benchmark. Coverage and evidence breadth still affect the composite; compare the evaluation conditions before reading a small score gap as decisive. “lab-reported” marks the provider's own published figure.
Sources: in and pending
in Reported (3)
- Aider polyglot · arrived Oct 8, 2026
- Epoch AI Benchmarking · arrived Oct 8, 2026
- Official model cards via models.dev · arrived Oct 8, 2026
pending Awaiting (2)
- LiveBench · carries 17% of expected weight
- LMArena / Arena · carries 34% of expected weight
The confidence % rises as pending sources publish. Some sources never cover some models — that is why 100% confidence arrives at 80% of expected weight, not at full coverage.