Preference · Anyscale

Llama 3 Anyscale 8B on Arena Elo: score, rank and what it means

Llama 3 Anyscale 8B scores 1251.4 on Arena Elo, placing it #489 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
1251.4
0–100 scale
Rank
#489
of 600
Percentile
19th
within the index
Benchmark avg
1349.9
all models
Leader
1501.9
Claude Opus 4.5 Max
Gap to leader
250.5
points

Score distribution

The chart shows the top 10 models on Arena Elo, with Llama 3 Anyscale 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, Llama 3 Anyscale 8B sits at #489 of 600. The leader, Claude Opus 4.5 Max, scores 1501.9, so the gap to the top is 250.5 points. The median model in this index scores 1373.8, which puts Llama 3 Anyscale 8B below the midpoint.

Anyscale models average 1315.0 on this benchmark. Llama 3 Anyscale 8B is 63.6 points below that provider line, so it is a weaker result than the average Anyscale model.

Among small open-weight models, the average is 1224.7. Llama 3 Anyscale 8B is 26.7 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 1251.4 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 $0.97 per million input tokens, Llama 3 Anyscale 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
Mistral Small 3 8B Mistral AI 8192 $0.99 57.2
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

Other benchmarks for Llama 3 Anyscale 8B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 60.8 515 14th
GPQA Diamond 53.8 484 19th
SWE-bench Verified 42.2 500 17th
HumanEval 59.3 511 15th
MATH-500 60.2 459 24th
AIME 2025 46.9 478 20th
LiveCodeBench 46.2 484 19th
IFEval 68.6 483 20th
TruthfulQA 62.2 500 17th
HellaSwag 73.5 466 22th
MMMU 56.8 475 21th

FAQ

What score does Llama 3 Anyscale 8B get on Arena Elo?

Llama 3 Anyscale 8B scores 1251.4 on Arena Elo in this index. The benchmark average is 1349.9 and the top score is 1501.9.

How does Llama 3 Anyscale 8B rank on Arena Elo?

It ranks #489 of 600 models, in the 19th percentile. The leader is Claude Opus 4.5 Max at 1501.9.

Is Llama 3 Anyscale 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 Llama 3 Anyscale 8B cost?

Llama 3 Anyscale 8B costs $0.97 per million input tokens and $4.27 per million output tokens.

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