Reasoning · Together AI

Llama 3.1 Turbo Chat on GPQA Diamond: score, rank and what it means

Llama 3.1 Turbo Chat scores 73.6 on GPQA Diamond, placing it #182 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
73.6
0–100 scale
Rank
#182
of 600
Percentile
70th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
13.4
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with Llama 3.1 Turbo Chat 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 Turbo Chat sits at #182 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 13.4 points. The median model in this index scores 68.8, which puts Llama 3.1 Turbo Chat above the midpoint.

Together AI models average 60.8 on this benchmark. Llama 3.1 Turbo Chat is 12.8 points above that provider line, so it is a stronger result than the average Together AI model.

Among multimodal models, the average is 73.5. Llama 3.1 Turbo Chat is 0.1 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 73.6 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 $3.95 per million input tokens, Llama 3.1 Turbo Chat 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
MiniMax-M2 Instruct MiniMax 128000 $5.11 79.4
MiniMax-Text Chat MiniMax 128000 $4.26 77.8
Sonar Max Perplexity 32768 $11.60 77.8
Claude Haiku 4.5 Vision Anthropic 128000 $13.01 79.2
Llama 3.1 Turbo Chat Together AI 200000 $3.95 76.1
Llama 3.3 Groq Groq 32768 $3.98 76.8
Hunyuan-Turbo Reasoning Tencent 128000 $11.89 77.5

Other benchmarks for Llama 3.1 Turbo Chat

BenchmarkScoreRankPercentileRelative
MMLU-Pro 80.8 155 74th
SWE-bench Verified 64.2 230 62th
HumanEval 80.9 216 64th
MATH-500 81.5 176 71th
AIME 2025 73.0 202 66th
LiveCodeBench 69.9 194 68th
IFEval 83.0 243 60th
TruthfulQA 76.0 307 49th
HellaSwag 83.7 294 51th
MMMU 70.9 275 54th
Arena Elo 1404.5 195 68th

FAQ

What score does Llama 3.1 Turbo Chat get on GPQA Diamond?

Llama 3.1 Turbo Chat scores 73.6 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does Llama 3.1 Turbo Chat rank on GPQA Diamond?

It ranks #182 of 600 models, in the 70th percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is Llama 3.1 Turbo Chat 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 3.1 Turbo Chat cost?

Llama 3.1 Turbo Chat costs $3.95 per million input tokens and $20.39 per million output tokens.

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