SI Index Data as of Oct 9, 2026

GPT-4.1 nano: Price, Context, Benchmarks, and Release Details

OpenAI provisional listing · first seen Oct 8, 2026 · score computed Oct 9, 2026, 01:09 UTC
32.1
SI Score (method si-v3-retained-evidence-2)
#137 of 140 ranked
82% confidence 82 percent, High confidence — 4 of 8 expected sources in
Coverage 66% of expected source weight · 100% confidence at 80% coverage

Pillar breakdown

Coding (weight 40 percent) 8.9
Math (weight 15 percent) 56.3
Preference (weight 15 percent) 60.4
Reasoning (weight 30 percent) 5.8

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
$0.10LiteLLMFirst-party API Standard token rate; MIT LiteLLM transcription. Provider documentation: https://developers.openai.com/api/docs/pricing. Exact endpoint only; cache/batch/long-context rates excluded Retrieved Oct 9, 2026 · MIT
Open source ↗
Output price / 1M
$0.40LiteLLMFirst-party API Standard token rate; MIT LiteLLM transcription. Provider documentation: https://developers.openai.com/api/docs/pricing. Exact endpoint only; cache/batch/long-context rates excluded Retrieved Oct 9, 2026 · MIT
Open source ↗
Context window
1Mmodels.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
Apr 14, 2025models.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

9 results
Benchmark Raw result Normalized (0–100) Pillar
aider polyglot 8.9%Aider polyglotPublished source fact [variant] Aider polyglot; 225 cases; 2 attemptsPublished Apr 14, 2025 Retrieved Oct 9, 2026 · Apache-2.0
Open source ↗ 		8.9 coding
arc agi v1 public eval 1.8%ARC PrizeARC Prize steward-published result; exact edition/subset; publication time is HTTP Last-Modified of the aggregate export, not the evaluation date. [variant] gpt-4-1-nano-2025-04-14Published Oct 6, 2026 Retrieved Oct 9, 2026 · factual citation
Open source ↗ 		1.8 reasoning
arc agi v1 semi private 0%ARC PrizeARC Prize steward-published result; exact edition/subset; publication time is HTTP Last-Modified of the aggregate export, not the evaluation date. [variant] gpt-4-1-nano-2025-04-14Published Oct 6, 2026 Retrieved Oct 9, 2026 · factual citation
Open source ↗ 		0.0 reasoning
arc agi v2 public eval 0%ARC PrizeARC Prize steward-published result; exact edition/subset; publication time is HTTP Last-Modified of the aggregate export, not the evaluation date. [variant] gpt-4-1-nano-2025-04-14Published Oct 6, 2026 Retrieved Oct 9, 2026 · factual citation
Open source ↗ 		0.0 reasoning
arc agi v2 semi private 0%ARC PrizeARC Prize steward-published result; exact edition/subset; publication time is HTTP Last-Modified of the aggregate export, not the evaluation date. [variant] gpt-4-1-nano-2025-04-14Published Oct 6, 2026 Retrieved Oct 9, 2026 · factual citation
Open source ↗ 		0.0 reasoning
gpqa diamond 48.9%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Apr 14, 2025 Retrieved Oct 9, 2026 · CC-BY
Open source ↗ 		48.9 reasoning
lmarena text 1284.8 eloLMArena / ArenaPublished source fact [variant] text / overallPublished Oct 2, 2026 Retrieved Oct 9, 2026 · CC-BY-4.0
Open source ↗ 		60.4 preference
math level 5 70.0%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Apr 14, 2025 Retrieved Oct 9, 2026 · CC-BY
Open source ↗ 		70.0 math
otis mock aime 2024 2025 28.9%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Apr 14, 2025 Retrieved Oct 9, 2026 · CC-BY
Open source ↗ 		28.9 math

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 (4)

  • Aider polyglot · arrived Oct 8, 2026
  • ARC Prize · arrived Oct 8, 2026
  • Epoch AI Benchmarking · arrived Oct 8, 2026
  • LMArena / Arena · arrived Oct 8, 2026

pending Awaiting (4)

  • Humanity’s Last Exam · carries 12% of expected weight
  • Official model cards via models.dev · carries 4% of expected weight
  • LiveBench · carries 12% of expected weight
  • Terminal-Bench · carries 6% 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.