Multimodal · Reka AI

Reka Core Nano on MMMU: score, rank and what it means

Reka Core Nano scores 61.8 on MMMU, placing it #411 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
61.8
0–100 scale
Rank
#411
of 600
Percentile
32th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
25.1
points

Score distribution

The chart shows the top 10 models on MMMU, with Reka Core Nano highlighted. Longer bars mean higher scores.

GPT-5.2 Max 86.9
GPT-5.1 Reasoning 86.2
GPT-5.2 85.3
Claude Sonnet 4.5 Reasoning 85.2
GPT-5.1 Max 85.1
Grok 4 Pro 84.9
Claude Opus 4.5 Reasoning 84.6
Claude Sonnet 4.5 Pro 84.5
GPT-5.2 Pro 84.4
GPT-5.2 Vision 84.4

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-5.2 OpenAI 2000000 $19.71 88.0
4 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
5 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
6 Grok 4 Pro xAI 1000000 $19.00 85.4
7 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
8 Claude Sonnet 4.5 Pro Anthropic 1000000 $18.73 86.7
9 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
10 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4

What this score means

On MMMU, Reka Core Nano sits at #411 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 25.1 points. The median model in this index scores 70.0, which puts Reka Core Nano below the midpoint.

Reka AI models average 70.7 on this benchmark. Reka Core Nano is 8.9 points below that provider line, so it is a weaker result than the average Reka AI model.

Among mid-range models, the average is 65.0. Reka Core Nano is 3.2 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 61.8 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 $5.45 per million input tokens, Reka Core Nano is above the median input price of $4.00 across the 600 models scored on MMMU. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Nemotron Nano Base NVIDIA 8192 $1.85 65.0
Zephyr Hugging Face 8192 $1.61 62.8
Nova Lite Mini Amazon 16384 $5.43 65.0
DeepSeek-R1 7B DeepSeek 32768 $1.79 63.0
Reka Core Nano Reka AI 16384 $5.45 65.1
Phi-3.5 Base Microsoft 65536 $2.24 66.6
Arctic Base Snowflake 32768 $2.27 67.5

Other benchmarks for Reka Core Nano

BenchmarkScoreRankPercentileRelative
MMLU-Pro 68.5 412 31th
GPQA Diamond 59.9 407 32th
SWE-bench Verified 50.2 421 30th
HumanEval 68.1 413 31th
MATH-500 69.3 385 36th
AIME 2025 57.3 404 33th
LiveCodeBench 58.7 381 37th
IFEval 74.8 401 33th
TruthfulQA 67.8 416 31th
HellaSwag 79.5 390 35th
Arena Elo 1310.8 407 32th

FAQ

What score does Reka Core Nano get on MMMU?

Reka Core Nano scores 61.8 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does Reka Core Nano rank on MMMU?

It ranks #411 of 600 models, in the 32nd percentile. The leader is GPT-5.2 Max at 86.9.

Is Reka Core Nano good at MMMU?

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 MMMU score calculated?

MMMU is a multimodal 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 Nano cost?

Reka Core Nano costs $5.45 per million input tokens and $25.25 per million output tokens.

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