Preference · Together AI

Mixtral Turbo Instruct on Arena Elo: score, rank and what it means

Mixtral Turbo Instruct scores 1356.6 on Arena Elo, placing it #351 of 600 models in the index. The benchmark average is 1349.9 and the leader is Claude Opus 4.5 Max at 1501.9.

Score
1356.6
0–100 scale
Rank
#351
of 600
Percentile
42th
within the index
Benchmark avg
1349.9
all models
Leader
1501.9
Claude Opus 4.5 Max
Gap to leader
145.3
points

Score distribution

The chart shows the top 10 models on Arena Elo, with Mixtral Turbo Instruct highlighted. Longer bars mean higher scores.

Claude Opus 4.5 Max 1501.9
GPT-5.2 Reasoning 1500.4
GPT-5.2 Turbo 1500.3
Claude Opus 4.5 Reasoning 1497.5
GPT-5.2 Max 1495.3
Gemini 3 Pro Turbo 1494.9
Grok 4 Max 1491.4
Claude Opus 4.5 1491.2
GPT-5.1 Pro 1490.0
Grok 4 Reasoning 1487.6

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
2 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
3 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
4 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
5 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
6 Gemini 3 Pro Turbo Google DeepMind 400000 $19.62 86.4
7 Grok 4 Max xAI 2000000 $19.70 86.6
8 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
9 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
10 Grok 4 Reasoning xAI 2000000 $19.67 87.8

What this score means

On Arena Elo, Mixtral Turbo Instruct sits at #351 of 600. The leader, Claude Opus 4.5 Max, scores 1501.9, so the gap to the top is 145.3 points. The median model in this index scores 1373.8, which puts Mixtral Turbo Instruct below the midpoint.

Together AI models average 1312.2 on this benchmark. Mixtral Turbo Instruct is 44.4 points above that provider line, so it is a stronger result than the average Together AI model.

Among open-weight models, the average is 1338.0. Mixtral Turbo Instruct is 18.6 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 1356.6 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 $3.16 per million input tokens, Mixtral Turbo Instruct is below the median input price of $4.00 across the 600 models scored on Arena Elo. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Firefunction Pro Fireworks AI 16384 $9.05 72.9
Fusion Reasoning OpenRouter 65536 $8.59 72.2
Firefunction Fireworks AI 16384 $8.16 72.3
Phi-3.5 Microsoft 16384 $2.81 70.9
Mixtral Turbo Instruct Together AI 32768 $3.16 71.9
Firefunction Turbo Fireworks AI 32768 $8.44 70.7
Auto Pro OpenRouter 8192 $8.41 71.2

Other benchmarks for Mixtral Turbo Instruct

BenchmarkScoreRankPercentileRelative
MMLU-Pro 72.9 369 39th
GPQA Diamond 69.7 276 54th
SWE-bench Verified 60.8 309 49th
HumanEval 74.2 355 41th
MATH-500 75.9 303 50th
AIME 2025 67.5 304 49th
LiveCodeBench 61.4 358 40th
IFEval 82.1 275 54th
TruthfulQA 77.2 276 54th
HellaSwag 82.5 336 44th
MMMU 66.6 365 39th

FAQ

What score does Mixtral Turbo Instruct get on Arena Elo?

Mixtral Turbo Instruct scores 1356.6 on Arena Elo in this index. The benchmark average is 1349.9 and the top score is 1501.9.

How does Mixtral Turbo Instruct rank on Arena Elo?

It ranks #351 of 600 models, in the 42nd percentile. The leader is Claude Opus 4.5 Max at 1501.9.

Is Mixtral Turbo Instruct good at Arena Elo?

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 Arena Elo score calculated?

Arena Elo is a preference 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 Mixtral Turbo Instruct cost?

Mixtral Turbo Instruct costs $3.16 per million input tokens and $13.04 per million output tokens.

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