Preference · DeepSeek

DeepSeek-V3.2 8B on Arena Elo: score, rank and what it means

DeepSeek-V3.2 8B scores 1308.4 on Arena Elo, placing it #410 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
1308.4
0–100 scale
Rank
#410
of 600
Percentile
32th
within the index
Benchmark avg
1349.9
all models
Leader
1501.9
Claude Opus 4.5 Max
Gap to leader
193.5
points

Score distribution

The chart shows the top 10 models on Arena Elo, with DeepSeek-V3.2 8B 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, DeepSeek-V3.2 8B sits at #410 of 600. The leader, Claude Opus 4.5 Max, scores 1501.9, so the gap to the top is 193.5 points. The median model in this index scores 1373.8, which puts DeepSeek-V3.2 8B below the midpoint.

DeepSeek models average 1363.3 on this benchmark. DeepSeek-V3.2 8B is 54.9 points below that provider line, so it is a weaker result than the average DeepSeek model.

Among small open-weight models, the average is 1224.7. DeepSeek-V3.2 8B is 83.7 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 1308.4 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 $2.02 per million input tokens, DeepSeek-V3.2 8B 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
Kimi K2 8B Moonshot AI 8192 $1.86 64.7
Reka Core Nano Reka AI 16384 $5.45 65.1
Embed 4 Reasoning Cohere 4096 $5.50 65.3
ERNIE 4.5 Nano Baidu 32768 $6.01 65.6
DeepSeek-V3.2 8B DeepSeek 32768 $2.02 66.2
Qwen3 8B Alibaba Cloud 8192 $1.66 61.9
Kimi K2 7B Moonshot AI 16384 $1.72 62.7

Other benchmarks for DeepSeek-V3.2 8B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 72.4 378 37th
GPQA Diamond 58.8 419 30th
SWE-bench Verified 55.2 382 36th
HumanEval 69.7 398 34th
MATH-500 66.7 410 32th
AIME 2025 56.4 409 32th
LiveCodeBench 58.9 379 37th
IFEval 76.0 388 35th
TruthfulQA 71.6 386 36th
HellaSwag 77.4 409 32th
MMMU 65.4 377 37th

FAQ

What score does DeepSeek-V3.2 8B get on Arena Elo?

DeepSeek-V3.2 8B scores 1308.4 on Arena Elo in this index. The benchmark average is 1349.9 and the top score is 1501.9.

How does DeepSeek-V3.2 8B rank on Arena Elo?

It ranks #410 of 600 models, in the 32nd percentile. The leader is Claude Opus 4.5 Max at 1501.9.

Is DeepSeek-V3.2 8B 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 DeepSeek-V3.2 8B cost?

DeepSeek-V3.2 8B costs $2.02 per million input tokens and $9.37 per million output tokens.

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