Reasoning · Together AI

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

Llama 3.1 Turbo Base scores 65.6 on GPQA Diamond, placing it #350 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
65.6
0–100 scale
Rank
#350
of 600
Percentile
42th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
21.4
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with Llama 3.1 Turbo 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 3.1 Turbo Base sits at #350 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 21.4 points. The median model in this index scores 68.8, which puts Llama 3.1 Turbo Base below the midpoint.

Together AI models average 60.8 on this benchmark. Llama 3.1 Turbo Base is 4.8 points above that provider line, so it is a stronger result than the average Together AI model.

Among open-weight models, the average is 63.6. Llama 3.1 Turbo Base is 2.0 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 65.6 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 $3.30 per million input tokens, Llama 3.1 Turbo 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
Mixtral Groq Instruct Groq 16384 $3.25 72.5
Reka Core Mini Reka AI 8192 $7.48 70.1
Yi-Lightning Base 01.AI 16384 $3.31 72.7
Arctic Chat Snowflake 16384 $2.70 69.8
Llama 3.1 Turbo Base Together AI 16384 $3.30 73.0
Llama 3.3 Groq Base Groq 16384 $3.24 73.5
Phi-3.5 Instruct Microsoft 16384 $2.67 70.1

Other benchmarks for Llama 3.1 Turbo Base

BenchmarkScoreRankPercentileRelative
MMLU-Pro 75.8 310 48th
SWE-bench Verified 62.2 275 54th
HumanEval 79.4 252 58th
MATH-500 76.8 284 53th
AIME 2025 68.3 290 52th
LiveCodeBench 66.5 264 56th
IFEval 79.6 342 43th
TruthfulQA 77.2 275 54th
HellaSwag 84.5 267 56th
MMMU 67.0 358 40th
Arena Elo 1381.0 271 55th

FAQ

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

Llama 3.1 Turbo Base scores 65.6 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 Base rank on GPQA Diamond?

It ranks #350 of 600 models, in the 42nd percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is Llama 3.1 Turbo Base 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 Turbo Base cost?

Llama 3.1 Turbo Base costs $3.30 per million input tokens and $13.59 per million output tokens.

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