Mathematics · DeepInfra

Llama 3 DeepInfra Base on MATH-500: score, rank and what it means

Llama 3 DeepInfra Base scores 75.9 on MATH-500, placing it #302 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
75.9
0–100 scale
Rank
#302
of 600
Percentile
50th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
20.8
points

Score distribution

The chart shows the top 10 models on MATH-500, with Llama 3 DeepInfra Base highlighted. Longer bars mean higher scores.

GPT-5.2 Max 96.7
GPT-5.1 Reasoning 95.9
GPT-5.1 Pro 95.1
o4 Reasoning 94.8
Grok 4 Max 94.6
Grok 4 Reasoning 94.4
Claude Opus 4.5 Max 94.2
Claude Opus 4.5 93.7
Gemini 3 Pro Reasoning 93.3
Claude Opus 4.5 Turbo 93.2

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
3 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
4 o4 Reasoning OpenAI 1000000 $19.69 87.5
5 Grok 4 Max xAI 2000000 $19.70 86.6
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
8 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
9 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
10 Claude Opus 4.5 Turbo Anthropic 2000000 $19.57 85.7

What this score means

On MATH-500, Llama 3 DeepInfra Base sits at #302 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 20.8 points. The median model in this index scores 76.0, which puts Llama 3 DeepInfra Base below the midpoint.

DeepInfra models average 67.0 on this benchmark. Llama 3 DeepInfra Base is 8.9 points above that provider line, so it is a stronger result than the average DeepInfra model.

Among open-weight models, the average is 70.8. Llama 3 DeepInfra Base is 5.1 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 75.9 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 $2.95 per million input tokens, Llama 3 DeepInfra Base is below the median input price of $4.00 across the 600 models scored on MATH-500. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Gemini 2.5 Pro Mini Google DeepMind 128000 $10.07 74.2
Llama 3 Anyscale Chat Anyscale 65536 $3.67 74.6
Llama 3 Replicate Chat Replicate 200000 $3.74 74.7
Llama 3 Baseten Base Baseten 16384 $3.16 72.4
Llama 3 DeepInfra Base DeepInfra 16384 $2.95 71.8
Mixtral Turbo Instruct Together AI 32768 $3.16 71.9
Llama 3 DeepInfra DeepInfra 128000 $3.67 74.0

Other benchmarks for Llama 3 DeepInfra Base

BenchmarkScoreRankPercentileRelative
MMLU-Pro 75.6 316 47th
GPQA Diamond 64.5 371 38th
SWE-bench Verified 58.2 352 41th
HumanEval 76.2 326 46th
AIME 2025 67.5 302 50th
LiveCodeBench 63.5 332 45th
IFEval 79.7 339 44th
TruthfulQA 77.0 282 53th
HellaSwag 83.8 287 52th
MMMU 67.6 351 42th
Arena Elo 1374.7 295 51th

FAQ

What score does Llama 3 DeepInfra Base get on MATH-500?

Llama 3 DeepInfra Base scores 75.9 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Llama 3 DeepInfra Base rank on MATH-500?

It ranks #302 of 600 models, in the 50th percentile. The leader is GPT-5.2 Max at 96.7.

Is Llama 3 DeepInfra Base good at MATH-500?

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 MATH-500 score calculated?

MATH-500 is a mathematics 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 DeepInfra Base cost?

Llama 3 DeepInfra Base costs $2.95 per million input tokens and $15.78 per million output tokens.

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