Reasoning · DeepInfra

Llama 3 DeepInfra Chat on GPQA Diamond: score, rank and what it means

Llama 3 DeepInfra Chat scores 69.0 on GPQA Diamond, placing it #295 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
69.0
0–100 scale
Rank
#295
of 600
Percentile
51th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
18.0
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with Llama 3 DeepInfra Chat highlighted. Longer bars mean higher scores.

GPT-5.2 Reasoning 87.0
GPT-5.1 Max 86.4
Claude Opus 4.5 Pro 86.0
GPT-5.1 Reasoning 85.6
Claude Sonnet 4.5 Reasoning 85.2
GPT-5.2 84.9
o4 Turbo 84.8
Claude Opus 4.5 Max 84.6
Grok 4 Turbo 84.5
Claude Sonnet 4.5 Max 84.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
5 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
6 GPT-5.2 OpenAI 2000000 $19.71 88.0
7 o4 Turbo OpenAI 2000000 $19.34 86.6
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 Grok 4 Turbo xAI 1000000 $19.21 86.7
10 Claude Sonnet 4.5 Max Anthropic 1000000 $19.90 87.2

What this score means

On GPQA Diamond, Llama 3 DeepInfra Chat sits at #295 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 18.0 points. The median model in this index scores 68.8, which puts Llama 3 DeepInfra Chat above the midpoint.

DeepInfra models average 60.7 on this benchmark. Llama 3 DeepInfra Chat is 8.3 points above that provider line, so it is a stronger result than the average DeepInfra model.

Among multimodal models, the average is 73.5. Llama 3 DeepInfra Chat is 4.5 points below that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 69.0 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 $3.74 per million input tokens, Llama 3 DeepInfra Chat is below the median input price of $4.00 across the 600 models scored on GPQA Diamond. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Auto Turbo OpenRouter 65536 $7.96 70.9
Hunyuan-Large Base Tencent 200000 $3.64 74.0
Llama 3 Lambda Instruct Lambda 32768 $3.92 75.8
Grok 4 Nano xAI 16384 $8.97 72.7
Llama 3 DeepInfra Chat DeepInfra 200000 $3.74 75.0
Nova Lite Reasoning Amazon 32768 $9.92 74.3
Yi-Large Chat 01.AI 65536 $3.49 73.5

Other benchmarks for Llama 3 DeepInfra Chat

BenchmarkScoreRankPercentileRelative
MMLU-Pro 76.8 281 53th
SWE-bench Verified 65.5 204 66th
HumanEval 77.3 304 49th
MATH-500 80.6 198 67th
AIME 2025 72.5 209 65th
LiveCodeBench 67.8 230 62th
IFEval 81.4 291 52th
TruthfulQA 78.3 244 59th
HellaSwag 83.6 299 50th
MMMU 72.1 240 60th
Arena Elo 1376.4 286 52th

FAQ

What score does Llama 3 DeepInfra Chat get on GPQA Diamond?

Llama 3 DeepInfra Chat scores 69.0 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does Llama 3 DeepInfra Chat rank on GPQA Diamond?

It ranks #295 of 600 models, in the 51st percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is Llama 3 DeepInfra Chat good at GPQA Diamond?

Yes, relative to the index: it is above the median and inside the top half of scores. The result should be read alongside its price and context window.

How is the GPQA Diamond score calculated?

GPQA Diamond is a reasoning 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 Chat cost?

Llama 3 DeepInfra Chat costs $3.74 per million input tokens and $15.32 per million output tokens.

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