Model comparison

GPT-5.5 Instant vs Llama 3.1-8B

GPT-5.5 Instant is the stronger model overall, scoring 42.7 to 23.0 on the Noometry Index.

Last verified . 23 shared benchmarks.

GPT-5.5 Instant OpenAI

42.7

Rank #110 Confirmed

Llama 3.1-8B Meta

23.0

Rank #352 Confirmed

Summary

  • They share 23 benchmarks with published results for both. GPT-5.5 Instant scores higher in 8 categories and Llama 3.1-8B in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GPT-5.5 Instant leads 48.9 to 8.0.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 68.1% for GPT-5.5 Instant and 1.7% for Llama 3.1-8B.
  • Llama 3.1-8B has downloadable open weights; the other is API-only.

Side by side

GPT-5.5 Instant and Llama 3.1-8B specifications
GPT-5.5 InstantLlama 3.1-8B
ProviderOpenAIMeta
Noometry Index42.723.0
Released2026-05-052024-07-23
WeightsProprietaryOpen
Context window—128K
Max output—4K
Input $ / M tokens—$0.05
Output $ / M tokens—$0.08
Results tracked2743

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Category by category

Coding GPT-5.5 Instant leads

GPT-5.5 Instant: 44.3 (#74), Llama 3.1-8B: 20.2 (#340)

Coding benchmarks
BenchmarkGPT-5.5 InstantLlama 3.1-8B
SciCode48.6%13.2%
LMArena Coding14331195
WeirdML—1.7%
BigCodeBench Instruct—32.8%
BigCodeBench Complete—40.5%
HumanEval+—62.8%
MBPP+—55.6%

Agentic & Tool Use Not comparable

GPT-5.5 Instant: —, Llama 3.1-8B: 22.5 (#131)

Agentic & Tool Use benchmarks
BenchmarkGPT-5.5 InstantLlama 3.1-8B
Berkeley Function Calling Leaderboard—25.8%
BALROG—15.1%

Reasoning GPT-5.5 Instant leads

GPT-5.5 Instant: 24.9 (#155), Llama 3.1-8B: 14.9 (#321)

Reasoning benchmarks
BenchmarkGPT-5.5 InstantLlama 3.1-8B
CritPt0%0%
Chess Puzzles12%0%
LMArena Hard Prompts14261175
Epoch Capabilities Index142.52116.57
DTBench—50.9%
LMCA—5.4%
PIQA—81.2%

Math GPT-5.5 Instant leads

GPT-5.5 Instant: 26.5 (#259), Llama 3.1-8B: 10.2 (#317)

Math benchmarks
BenchmarkGPT-5.5 InstantLlama 3.1-8B
OTIS Mock AIME 2024-202568.1%1.7%
LMArena Math14201179
FrontierMath (Tiers 1-3)26.3%—
FrontierMath Tier 42.4%—
Omni-MATH—13.7%
MATH Level 5—22.9%
GSM8K—82.4%

Knowledge GPT-5.5 Instant leads

GPT-5.5 Instant: 48.9 (#74), Llama 3.1-8B: 8.0 (#307)

Knowledge benchmarks
BenchmarkGPT-5.5 InstantLlama 3.1-8B
GPQA Diamond82.5%27%
LMArena Expert14091144
MMLU-Pro—40.6%
GPQA (HELM)—24.7%
BoolQ—82.8%
MMLU—56.1%

Multimodal Not comparable

GPT-5.5 Instant: 40.0 (#52), Llama 3.1-8B: —

Multimodal benchmarks
BenchmarkGPT-5.5 InstantLlama 3.1-8B
LMArena Vision1250—
LMArena Document1403—

Multilingual GPT-5.5 Instant leads

GPT-5.5 Instant: 52.8 (#80), Llama 3.1-8B: 34.0 (#249)

Multilingual benchmarks
BenchmarkGPT-5.5 InstantLlama 3.1-8B
LMArena Non-English14171148
LMArena Chinese14561151
LMArena French14281177
LMArena German14111144
LMArena Japanese14081061
LMArena Korean13921053
LMArena Russian14311158
LMArena Spanish14291169

Instruction Following GPT-5.5 Instant leads

GPT-5.5 Instant: 74.2 (#100), Llama 3.1-8B: 58.9 (#258)

Instruction Following benchmarks
BenchmarkGPT-5.5 InstantLlama 3.1-8B
LMArena Instruction Following14061159
IFEval—74.3%

Long Context GPT-5.5 Instant leads

GPT-5.5 Instant: 43.4 (#96), Llama 3.1-8B: 35.8 (#238)

Long Context benchmarks
BenchmarkGPT-5.5 InstantLlama 3.1-8B
LMArena Longer Query14221182

Writing & Preference GPT-5.5 Instant leads

GPT-5.5 Instant: 61.8 (#85), Llama 3.1-8B: 29.7 (#290)

Writing & Preference benchmarks
BenchmarkGPT-5.5 InstantLlama 3.1-8B
LMArena Text14191187
LMArena Creative Writing14191154
LMArena Multi-Turn14331172
EQ-Bench Creative Writing—713
WildBench—68.7%

Frequently asked questions

Is GPT-5.5 Instant better than Llama 3.1-8B?

GPT-5.5 Instant is the stronger model overall, scoring 42.7 to 23.0 on the Noometry Index.

Is GPT-5.5 Instant or Llama 3.1-8B better for coding?

GPT-5.5 Instant scores higher on coding benchmarks: 44.3 versus 20.2 in the Noometry coding category.

How many benchmarks do GPT-5.5 Instant and Llama 3.1-8B share?

23 benchmarks have published results for both models. GPT-5.5 Instant has 27 scored results on Noometry and Llama 3.1-8B has 43.

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