Reasoning · Meta AI

Llama 3.1 7B on GPQA Diamond: score, rank and what it means

Llama 3.1 7B scores 54.4 on GPQA Diamond, placing it #474 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
54.4
0–100 scale
Rank
#474
of 600
Percentile
21th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
32.6
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with Llama 3.1 7B highlighted. Longer bars mean higher scores.

GPT-5.2 Reasoning 87.0
GPT-5.1 Max 86.4
Claude Opus 4.5 Pro 86.0
GPT-5.1 Reasoning 85.6
Claude Sonnet 4.5 Reasoning 85.2
GPT-5.2 84.9
o4 Turbo 84.8
Claude Opus 4.5 Max 84.6
Grok 4 Turbo 84.5
Claude Sonnet 4.5 Max 84.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
5 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
6 GPT-5.2 OpenAI 2000000 $19.71 88.0
7 o4 Turbo OpenAI 2000000 $19.34 86.6
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 Grok 4 Turbo xAI 1000000 $19.21 86.7
10 Claude Sonnet 4.5 Max Anthropic 1000000 $19.90 87.2

What this score means

On GPQA Diamond, Llama 3.1 7B sits at #474 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 32.6 points. The median model in this index scores 68.8, which puts Llama 3.1 7B below the midpoint.

Meta AI models average 64.6 on this benchmark. Llama 3.1 7B is 10.2 points below that provider line, so it is a weaker result than the average Meta AI model.

Among small open-weight models, the average is 49.3. Llama 3.1 7B is 5.1 points above that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 54.4 as a relative signal, not an absolute guarantee. Benchmark scores depend on prompt format, evaluation harness and contamination controls. Use this page to narrow the shortlist, then test the model on your own data.

Price context

At $1.01 per million input tokens, Llama 3.1 7B is below the median input price of $4.00 across the 600 models scored on GPQA Diamond. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Llama 3.1 Cerebras 8B Cerebras 32768 $1.02 58.2
MiniMax-Text 7B MiniMax 16384 $1.10 57.7
GLM-4.5 7B Zhipu AI 8192 $1.32 60.2
Seed-OSS 8B ByteDance 8192 $1.05 57.1
Llama 3.1 7B Meta AI 8192 $1.01 57.4
DeepSeek-R1 1.5B DeepSeek 16384 $1.04 56.6
GLM-4.5 8B Zhipu AI 32768 $1.46 61.3

Other benchmarks for Llama 3.1 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 64.8 456 24th
SWE-bench Verified 44.1 477 21th
HumanEval 60.4 498 17th
MATH-500 58.8 481 20th
AIME 2025 46.9 480 20th
LiveCodeBench 45.0 499 17th
IFEval 67.5 494 18th
TruthfulQA 63.8 473 21th
HellaSwag 71.1 518 14th
MMMU 54.5 503 16th
Arena Elo 1237.4 518 14th

FAQ

What score does Llama 3.1 7B get on GPQA Diamond?

Llama 3.1 7B scores 54.4 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does Llama 3.1 7B rank on GPQA Diamond?

It ranks #474 of 600 models, in the 21st percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is Llama 3.1 7B good at GPQA Diamond?

It is below the median for this benchmark, so test it carefully before relying on it for this capability. The result should be read alongside its price and context window.

How is the GPQA Diamond score calculated?

GPQA Diamond is a reasoning benchmark. Scores in this index are modelled estimates on a 0–100 scale (or Elo for Arena), derived from capability tier and benchmark difficulty. They are not official leaderboard results.

What does Llama 3.1 7B cost?

Llama 3.1 7B costs $1.01 per million input tokens and $3.79 per million output tokens.

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