Knowledge · Reka AI

Reka Core on MMLU-Pro: score, rank and what it means

Reka Core scores 80.0 on MMLU-Pro, placing it #185 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
80.0
0–100 scale
Rank
#185
of 600
Percentile
69th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
11.6
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Reka Core highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 91.6
GPT-5.1 Max 91.3
Claude Opus 4.5 Pro 91.2
Claude Opus 4.5 Reasoning 90.7
Gemini 3 Pro Reasoning 90.1
GPT-5.1 Reasoning 90.0
GPT-5.2 89.9
Claude Opus 4.5 Max 89.5
GPT-5.2 Vision 89.5
Gemini 3 Pro Max 89.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
5 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
6 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
7 GPT-5.2 OpenAI 2000000 $19.71 88.0
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4
10 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9

What this score means

On MMLU-Pro, Reka Core sits at #185 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 11.6 points. The median model in this index scores 76.1, which puts Reka Core above the midpoint.

Reka AI models average 76.2 on this benchmark. Reka Core is 3.8 points above that provider line, so it is a stronger result than the average Reka AI model.

Among multimodal models, the average is 80.0. Reka Core is 0.0 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 80.0 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 $12.17 per million input tokens, Reka Core is above the median input price of $4.00 across the 600 models scored on MMLU-Pro. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Nova Pro Amazon 32768 $12.75 79.4
Llama 3 Baseten Instruct Baseten 200000 $3.91 76.2
Llama 4 Scout Instruct Meta AI 32768 $4.59 79.1
MiniMax-M2 Base MiniMax 65536 $4.20 76.4
Reka Core Reka AI 32768 $12.17 77.4
Llama 3.1 Chat Meta AI 32768 $3.82 75.3
Command R+ Instruct Cohere 200000 $4.16 76.2

Other benchmarks for Reka Core

BenchmarkScoreRankPercentileRelative
GPQA Diamond 74.8 148 75th
SWE-bench Verified 63.8 238 60th
HumanEval 82.0 187 69th
MATH-500 83.8 130 78th
AIME 2025 72.2 217 64th
LiveCodeBench 69.5 202 66th
IFEval 85.7 169 72th
TruthfulQA 79.0 221 63th
HellaSwag 87.1 175 71th
MMMU 73.4 209 65th
Arena Elo 1422.8 136 77th

FAQ

What score does Reka Core get on MMLU-Pro?

Reka Core scores 80.0 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does Reka Core rank on MMLU-Pro?

It ranks #185 of 600 models, in the 69th percentile. The leader is GPT-5.2 Pro at 91.6.

Is Reka Core good at MMLU-Pro?

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 MMLU-Pro score calculated?

MMLU-Pro is a knowledge 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 Reka Core cost?

Reka Core costs $12.17 per million input tokens and $55.77 per million output tokens.

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