Coding · Together AI

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

Llama 3.1 Turbo Chat scores 69.9 on LiveCodeBench, placing it #194 of 600 models in the index. The benchmark average is 61.0 and the leader is Claude Sonnet 4.5 Reasoning at 85.1.

Score
69.9
0–100 scale
Rank
#194
of 600
Percentile
68th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
15.2
points

Score distribution

The chart shows the top 10 models on LiveCodeBench, with Llama 3.1 Turbo Chat highlighted. Longer bars mean higher scores.

Claude Sonnet 4.5 Reasoning 85.1
Grok 4 Reasoning 85.1
Claude Opus 4.5 85.0
GPT-5.2 Max 84.8
Grok 4 Turbo 84.7
GPT-5.1 Turbo 84.6
GPT-5.2 Pro 84.6
GPT-5.2 Reasoning 84.6
Claude Opus 4.5 Pro 84.1
Gemini 3 Pro Max 83.6

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
2 Grok 4 Reasoning xAI 2000000 $19.67 87.8
3 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
4 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
5 Grok 4 Turbo xAI 1000000 $19.21 86.7
6 GPT-5.1 Turbo OpenAI 2000000 $19.19 86.1
7 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
8 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
9 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
10 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9

What this score means

On LiveCodeBench, Llama 3.1 Turbo Chat sits at #194 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 15.2 points. The median model in this index scores 64.7, which puts Llama 3.1 Turbo Chat above the midpoint.

Together AI models average 54.9 on this benchmark. Llama 3.1 Turbo Chat is 15.0 points above that provider line, so it is a stronger result than the average Together AI model.

Among multimodal models, the average is 70.3. Llama 3.1 Turbo Chat is 0.4 points below 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 $3.95 per million input tokens, Llama 3.1 Turbo Chat is below the median input price of $4.00 across the 600 models scored on LiveCodeBench. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Llama 3 Lambda Lambda 65536 $3.90 75.6
Nemotron 4 NVIDIA 65536 $4.18 76.6
Kimi K2 Base Moonshot AI 65536 $4.82 79.2
Llama 3.1 Turbo Together AI 200000 $4.17 76.8
Llama 3.1 Turbo Chat Together AI 200000 $3.95 76.1
Phi-4 Instruct Microsoft 128000 $3.79 75.3
Qwen3-Coder Alibaba Cloud 200000 $4.94 79.5

Other benchmarks for Llama 3.1 Turbo Chat

BenchmarkScoreRankPercentileRelative
MMLU-Pro 80.8 155 74th
GPQA Diamond 73.6 182 70th
SWE-bench Verified 64.2 230 62th
HumanEval 80.9 216 64th
MATH-500 81.5 176 71th
AIME 2025 73.0 202 66th
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 LiveCodeBench?

Llama 3.1 Turbo Chat scores 69.9 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does Llama 3.1 Turbo Chat rank on LiveCodeBench?

It ranks #194 of 600 models, in the 68th percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is Llama 3.1 Turbo Chat good at LiveCodeBench?

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 LiveCodeBench score calculated?

LiveCodeBench is a coding 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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