GPT OSS 120B: Price, Context, Benchmarks, and Release Details
54.8
SI Score (method si-v3-retained-evidence-2)
#89 of 140 ranked
79% confidence 79 percent, Medium confidence — 5 of 10 expected sources in
Coverage 63% of expected source weight · 100% confidence at 80% coverage
Pillar breakdown
Coding (weight 40 percent) 28.0
Math (weight 15 percent) 88.9
Preference (weight 15 percent) 69.6
Reasoning (weight 30 percent) 75.8
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
- not yet reported
- Output price / 1M
- not yet reported
- Context window
- 131Kmodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Max output
- 32.8Kmodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Released
- Aug 5, 2025models.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Open weights
- Yesmodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - License
- not yet reported
- Input modalities
- textmodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗
Benchmark results
6 results| Benchmark | Raw result | Normalized (0–100) | Pillar |
|---|---|---|---|
| aider polyglot | 41.8%Aider polyglotPublished source fact [variant] Aider polyglot; 225 cases; 2 attemptsPublished Aug 6, 2025
Retrieved Oct 9, 2026 · Apache-2.0 Open source ↗ | 41.8 | coding |
| gpqa diamond | 75.8%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] highPublished Dec 11, 2025
Retrieved Oct 9, 2026 · CC-BY Open source ↗ | 75.8 | reasoning |
| lmarena text | 1365.4 eloLMArena / ArenaPublished source fact [variant] text / overallPublished Oct 2, 2026
Retrieved Oct 9, 2026 · CC-BY-4.0 Open source ↗ | 69.6 | preference |
| otis mock aime 2024 2025 | 88.9%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] highPublished Dec 11, 2025
Retrieved Oct 9, 2026 · CC-BY Open source ↗ | 88.9 | math |
| swe bench pro public | 16.2%SWE-bench Pro (public)Published steward score [variant] Published Jan 27, 2026
Retrieved Oct 9, 2026 · factual citation Open source ↗ | 16.2 | coding |
| swe bench verified | 26%SWE-bench VerifiedSWE-bench published model plus agent result; harness retained, not a base model evaluation [variant] mini-SWE-agent; 1.7.0Published Aug 7, 2025
Retrieved Oct 9, 2026 · factual citation Open source ↗ | 26.0 | 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 (5)
- Aider polyglot · arrived Oct 8, 2026
- Epoch AI Benchmarking · arrived Oct 8, 2026
- LMArena / Arena · arrived Oct 8, 2026
- SWE-bench Verified · arrived Oct 8, 2026
- SWE-bench Pro (public) · arrived Oct 8, 2026
pending Awaiting (5)
- ARC Prize · carries 10% of expected weight
- Humanity’s Last Exam · carries 10% of expected weight
- Official model cards via models.dev · carries 3% of expected weight
- LiveBench · carries 10% of expected weight
- Terminal-Bench · carries 5% 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.