Commonsense · Together AI

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

Llama 3.1 Turbo Chat scores 83.7 on HellaSwag, placing it #294 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
83.7
0–100 scale
Rank
#294
of 600
Percentile
51th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
12.4
points

Score distribution

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

GPT-5.2 Max 96.1
GPT-5.2 Turbo 95.5
GPT-5.2 Pro 95.3
Claude Opus 4.5 Pro 95.2
Claude Sonnet 4.5 Reasoning 95.2
Grok 4 Reasoning 95.2
GPT-5.2 Vision 94.6
Gemini 3 Pro Turbo 94.6
GPT-5.1 Reasoning 94.4
o4 Pro 94.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
3 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
4 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
5 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4
8 Gemini 3 Pro Turbo Google DeepMind 400000 $19.62 86.4
9 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
10 o4 Pro OpenAI 1000000 $19.37 87.3

What this score means

On HellaSwag, Llama 3.1 Turbo Chat sits at #294 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 12.4 points. The median model in this index scores 83.6, which puts Llama 3.1 Turbo Chat above the midpoint.

Together AI models average 78.2 on this benchmark. Llama 3.1 Turbo Chat is 5.5 points above that provider line, so it is a stronger result than the average Together AI model.

Among multimodal models, the average is 86.8. Llama 3.1 Turbo Chat is 3.1 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 83.7 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 $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 HellaSwag. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Gemma 3 Google DeepMind 65536 $3.68 73.6
Llama 3 Anyscale Base Anyscale 65536 $3.23 72.9
Llama 3 Lambda Lambda 65536 $3.90 75.6
Llama 3.1 Chat Meta AI 32768 $3.82 75.3
Llama 3.1 Turbo Chat Together AI 200000 $3.95 76.1
Mixtral Chat Mistral AI 65536 $3.30 72.6
Seed-OSS Base ByteDance 16384 $3.14 72.2

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
LiveCodeBench 69.9 194 68th
IFEval 83.0 243 60th
TruthfulQA 76.0 307 49th
MMMU 70.9 275 54th
Arena Elo 1404.5 195 68th

FAQ

What score does Llama 3.1 Turbo Chat get on HellaSwag?

Llama 3.1 Turbo Chat scores 83.7 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does Llama 3.1 Turbo Chat rank on HellaSwag?

It ranks #294 of 600 models, in the 51st percentile. The leader is GPT-5.2 Max at 96.1.

Is Llama 3.1 Turbo Chat good at HellaSwag?

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 HellaSwag score calculated?

HellaSwag is a commonsense 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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