Reasoning · 01.AI

Yi-Large 7B on GPQA Diamond: score, rank and what it means

Yi-Large 7B scores 50.0 on GPQA Diamond, placing it #524 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
50.0
0–100 scale
Rank
#524
of 600
Percentile
13th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
37.0
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with Yi-Large 7B 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, Yi-Large 7B sits at #524 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 37.0 points. The median model in this index scores 68.8, which puts Yi-Large 7B below the midpoint.

01.AI models average 61.2 on this benchmark. Yi-Large 7B is 11.2 points below that provider line, so it is a weaker result than the average 01.AI model.

Among small open-weight models, the average is 49.3. Yi-Large 7B is 0.7 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 50.0 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 $0.83 per million input tokens, Yi-Large 7B 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 Nano OpenRouter 4096 $2.83 57.1
Llama 4 Scout 1.5B Meta AI 8192 $0.66 53.0
Llama 3 Hyperbolic 7B Hyperbolic 4096 $0.94 55.6
DBRX 7B Databricks 8192 $0.65 51.9
Yi-Large 7B 01.AI 4096 $0.83 55.0
MiniMax-M2 1.5B MiniMax 16384 $0.84 54.6
Llama 3 Anyscale 7B Anyscale 4096 $0.98 56.2

Other benchmarks for Yi-Large 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 61.2 510 15th
SWE-bench Verified 41.6 505 16th
HumanEval 60.0 505 16th
MATH-500 57.3 496 17th
AIME 2025 45.9 490 18th
LiveCodeBench 42.8 520 13th
IFEval 64.9 533 11th
TruthfulQA 59.6 535 11th
HellaSwag 69.8 538 10th
MMMU 51.7 537 11th
Arena Elo 1218.0 536 11th

FAQ

What score does Yi-Large 7B get on GPQA Diamond?

Yi-Large 7B scores 50.0 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does Yi-Large 7B rank on GPQA Diamond?

It ranks #524 of 600 models, in the 13th percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is Yi-Large 7B good at GPQA Diamond?

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 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 Yi-Large 7B cost?

Yi-Large 7B costs $0.83 per million input tokens and $3.25 per million output tokens.

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