Reasoning · Meta AI

Llama 3.3 7B on GPQA Diamond: score, rank and what it means

Llama 3.3 7B scores 51.7 on GPQA Diamond, placing it #503 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
51.7
0–100 scale
Rank
#503
of 600
Percentile
16th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
35.3
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with Llama 3.3 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 3.3 7B sits at #503 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 35.3 points. The median model in this index scores 68.8, which puts Llama 3.3 7B below the midpoint.

Meta AI models average 64.6 on this benchmark. Llama 3.3 7B is 12.9 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 3.3 7B is 2.4 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 51.7 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 $1.18 per million input tokens, Llama 3.3 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
Yi-Large 8B 01.AI 32768 $0.88 56.1
Llama 3.1 Turbo 7B Together AI 8192 $0.98 56.4
Mistral Small 3 8B Mistral AI 8192 $0.99 57.2
Llama 3.1 Cerebras 7B Cerebras 32768 $0.95 56.5
Llama 3.3 7B Meta AI 8192 $1.18 57.8
Seed-OSS 7B ByteDance 8192 $0.85 55.5
Nemotron 4 7B NVIDIA 16384 $1.05 56.9

Other benchmarks for Llama 3.3 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 62.8 491 18th
SWE-bench Verified 43.4 486 19th
HumanEval 61.0 490 18th
MATH-500 62.0 445 26th
AIME 2025 46.3 487 19th
LiveCodeBench 47.1 474 21th
IFEval 67.2 500 17th
TruthfulQA 63.2 486 19th
HellaSwag 72.1 493 18th
MMMU 59.0 439 27th
Arena Elo 1269.1 461 23th

FAQ

What score does Llama 3.3 7B get on GPQA Diamond?

Llama 3.3 7B scores 51.7 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does Llama 3.3 7B rank on GPQA Diamond?

It ranks #503 of 600 models, in the 16th percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is Llama 3.3 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 3.3 7B cost?

Llama 3.3 7B costs $1.18 per million input tokens and $5.59 per million output tokens.

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