Preference · DeepSeek

DeepSeek-R1 1.5B on Arena Elo: score, rank and what it means

DeepSeek-R1 1.5B scores 1250.5 on Arena Elo, placing it #490 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
1250.5
0–100 scale
Rank
#490
of 600
Percentile
18th
within the index
Benchmark avg
1349.9
all models
Leader
1501.9
Claude Opus 4.5 Max
Gap to leader
251.4
points

Score distribution

The chart shows the top 10 models on Arena Elo, with DeepSeek-R1 1.5B 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-R1 1.5B sits at #490 of 600. The leader, Claude Opus 4.5 Max, scores 1501.9, so the gap to the top is 251.4 points. The median model in this index scores 1373.8, which puts DeepSeek-R1 1.5B below the midpoint.

DeepSeek models average 1363.3 on this benchmark. DeepSeek-R1 1.5B is 112.8 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-R1 1.5B is 25.8 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 1250.5 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 $1.04 per million input tokens, DeepSeek-R1 1.5B 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
Codestral 8B Mistral AI 4096 $1.18 59.0
Mixtral 8B Mistral AI 8192 $0.91 55.4
Hunyuan-Large 7B Tencent 32768 $1.08 57.7
Llama 3 Anyscale 8B Anyscale 32768 $0.97 57.3
DeepSeek-R1 1.5B DeepSeek 16384 $1.04 56.6
Llama 3 Novita 7B Novita AI 8192 $0.92 56.3
Llama 3 Hyperbolic 7B Hyperbolic 4096 $0.94 55.6

Other benchmarks for DeepSeek-R1 1.5B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 60.7 518 14th
GPQA Diamond 54.3 475 21th
SWE-bench Verified 45.2 464 23th
HumanEval 59.7 508 15th
MATH-500 58.5 484 19th
AIME 2025 42.7 527 12th
LiveCodeBench 42.9 516 14th
IFEval 66.6 506 16th
TruthfulQA 61.4 514 14th
HellaSwag 74.2 452 25th
MMMU 56.2 484 19th

FAQ

What score does DeepSeek-R1 1.5B get on Arena Elo?

DeepSeek-R1 1.5B scores 1250.5 on Arena Elo in this index. The benchmark average is 1349.9 and the top score is 1501.9.

How does DeepSeek-R1 1.5B rank on Arena Elo?

It ranks #490 of 600 models, in the 18th percentile. The leader is Claude Opus 4.5 Max at 1501.9.

Is DeepSeek-R1 1.5B 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-R1 1.5B cost?

DeepSeek-R1 1.5B costs $1.04 per million input tokens and $5.02 per million output tokens.

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