Reasoning · Anyscale

Llama 3 Anyscale Base on GPQA Diamond: score, rank and what it means

Llama 3 Anyscale Base scores 69.9 on GPQA Diamond, placing it #267 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
69.9
0–100 scale
Rank
#267
of 600
Percentile
56th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
17.1
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with Llama 3 Anyscale Base 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 Anyscale Base sits at #267 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 17.1 points. The median model in this index scores 68.8, which puts Llama 3 Anyscale Base above the midpoint.

Anyscale models average 61.3 on this benchmark. Llama 3 Anyscale Base is 8.6 points above that provider line, so it is a stronger result than the average Anyscale model.

Among open-weight models, the average is 63.6. Llama 3 Anyscale Base is 6.3 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 69.9 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 $3.23 per million input tokens, Llama 3 Anyscale Base 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 Novita Novita AI 128000 $3.70 74.4
Mistral Small 3 Instruct Mistral AI 32768 $3.97 75.1
Yi-Large Instruct 01.AI 32768 $3.48 73.4
Gemini 2.5 Pro Mini Google DeepMind 128000 $10.07 74.2
Llama 3 Anyscale Base Anyscale 65536 $3.23 72.9
QwQ Base Alibaba Cloud 65536 $3.68 74.1
Sonar Pro Perplexity 65536 $11.25 77.1

Other benchmarks for Llama 3 Anyscale Base

BenchmarkScoreRankPercentileRelative
MMLU-Pro 74.7 340 43th
SWE-bench Verified 58.3 350 42th
HumanEval 75.6 333 45th
MATH-500 77.0 276 54th
AIME 2025 69.2 275 54th
LiveCodeBench 63.5 331 45th
IFEval 81.6 283 53th
TruthfulQA 77.8 258 57th
HellaSwag 83.7 291 52th
MMMU 70.4 284 53th
Arena Elo 1379.8 273 55th

FAQ

What score does Llama 3 Anyscale Base get on GPQA Diamond?

Llama 3 Anyscale Base scores 69.9 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does Llama 3 Anyscale Base rank on GPQA Diamond?

It ranks #267 of 600 models, in the 56th percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is Llama 3 Anyscale Base good at GPQA Diamond?

Yes, relative to the index: it is above the median and inside the top half of scores. 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 Anyscale Base cost?

Llama 3 Anyscale Base costs $3.23 per million input tokens and $14.41 per million output tokens.

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