Multimodal · Reka AI

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

Reka Flash Nano scores 58.8 on MMMU, placing it #445 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
58.8
0–100 scale
Rank
#445
of 600
Percentile
26th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
28.1
points

Score distribution

The chart shows the top 10 models on MMMU, with Reka Flash 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 Flash Nano sits at #445 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 28.1 points. The median model in this index scores 70.0, which puts Reka Flash Nano below the midpoint.

Reka AI models average 70.7 on this benchmark. Reka Flash Nano is 11.9 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 Flash Nano is 6.2 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 58.8 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 $3.93 per million input tokens, Reka Flash Nano is below 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
Hunyuan-Large 8B Tencent 4096 $1.29 58.7
MiniMax-M2 7B MiniMax 8192 $1.44 60.8
Mistral Large 3 7B Mistral AI 32768 $1.44 61.1
Qwen3-Coder 8B Alibaba Cloud 32768 $1.43 61.3
Reka Flash Nano Reka AI 16384 $3.93 61.0
Llama 4 Maverick 7B Meta AI 4096 $1.52 61.9
Magistral 8B Mistral AI 4096 $1.33 60.0

Other benchmarks for Reka Flash Nano

BenchmarkScoreRankPercentileRelative
MMLU-Pro 66.4 435 28th
GPQA Diamond 59.0 417 31th
SWE-bench Verified 48.7 433 28th
HumanEval 65.9 431 28th
MATH-500 61.5 448 25th
AIME 2025 52.4 441 27th
LiveCodeBench 50.6 441 27th
IFEval 69.9 463 23th
TruthfulQA 63.6 481 20th
HellaSwag 74.6 449 25th
Arena Elo 1267.9 464 23th

FAQ

What score does Reka Flash Nano get on MMMU?

Reka Flash Nano scores 58.8 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does Reka Flash Nano rank on MMMU?

It ranks #445 of 600 models, in the 26th percentile. The leader is GPT-5.2 Max at 86.9.

Is Reka Flash 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 Flash Nano cost?

Reka Flash Nano costs $3.93 per million input tokens and $16.57 per million output tokens.

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