SI Index Data as of Oct 8, 2026

GPT-4o (2024-08-06): Price, Context, Benchmarks, and Release Details

OpenAI provisional listing · first seen Oct 8, 2026 · score computed Oct 8, 2026, 22:13 UTC
38.8
SI Score (method si-v2-absolute-shrinkage-1)
#109 of 115 ranked
88% confidence 88 percent, High confidence — 2 of 3 expected sources in
Coverage 70% of expected source weight · 100% confidence at 80% coverage

Pillar breakdown

Coding (weight 40 percent) 17.0
Math (weight 15 percent) 22.7
Preference (weight 15 percent) 60.2
Reasoning (weight 30 percent) 49.2

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
128Kmodels.devPublished source fact Retrieved Oct 8, 2026 · MIT
Open source ↗
Max output
16.4Kmodels.devPublished source fact Retrieved Oct 8, 2026 · MIT
Open source ↗
Released
Aug 6, 2024models.devPublished source fact Retrieved Oct 8, 2026 · MIT
Open source ↗
Open weights
Nomodels.devPublished source fact Retrieved Oct 8, 2026 · MIT
Open source ↗
License
not yet reported
Input modalities
text, imagemodels.devPublished source fact Retrieved Oct 8, 2026 · MIT
Open source ↗

Benchmark results

7 results
Benchmark Raw result Normalized (0–100) Pillar
aider polyglot 23.1%Aider polyglotPublished source fact [variant] Aider polyglot; 225 cases; 2 attemptsPublished Dec 30, 2024 Retrieved Oct 8, 2026 · Apache-2.0
Open source ↗ 		23.1 coding
frontiermath tiers 1 3 v2 0.4%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Aug 27, 2026 Retrieved Oct 8, 2026 · CC-BY
Open source ↗ 		0.4 math
gpqa diamond 49.2%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Jan 27, 2025 Retrieved Oct 8, 2026 · CC-BY
Open source ↗ 		49.2 reasoning
lmarena text 1282.5 eloLMArena / ArenaPublished source fact [variant] text / overallPublished Oct 2, 2026 Retrieved Oct 8, 2026 · CC-BY-4.0
Open source ↗ 		60.2 preference
math level 5 53.3%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Jan 27, 2025 Retrieved Oct 8, 2026 · CC-BY
Open source ↗ 		53.3 math
otis mock aime 2024 2025 6.4%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Feb 25, 2025 Retrieved Oct 8, 2026 · CC-BY
Open source ↗ 		6.4 math
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 8, 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 (2)

  • Official model cards via models.dev · arrived Oct 8, 2026
  • LMArena / Arena · arrived Oct 8, 2026

pending Awaiting (1)

  • LiveBench · carries 30% 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.