Mathematics · Reka AI

Reka Flash Turbo on MATH-500: score, rank and what it means

Reka Flash Turbo scores 75.3 on MATH-500, placing it #321 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
75.3
0–100 scale
Rank
#321
of 600
Percentile
47th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
21.4
points

Score distribution

The chart shows the top 10 models on MATH-500, with Reka Flash Turbo highlighted. Longer bars mean higher scores.

GPT-5.2 Max 96.7
GPT-5.1 Reasoning 95.9
GPT-5.1 Pro 95.1
o4 Reasoning 94.8
Grok 4 Max 94.6
Grok 4 Reasoning 94.4
Claude Opus 4.5 Max 94.2
Claude Opus 4.5 93.7
Gemini 3 Pro Reasoning 93.3
Claude Opus 4.5 Turbo 93.2

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-5.1 Pro OpenAI 200000 $19.77 87.8
4 o4 Reasoning OpenAI 1000000 $19.69 87.5
5 Grok 4 Max xAI 2000000 $19.70 86.6
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
8 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
9 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
10 Claude Opus 4.5 Turbo Anthropic 2000000 $19.57 85.7

What this score means

On MATH-500, Reka Flash Turbo sits at #321 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 21.4 points. The median model in this index scores 76.0, which puts Reka Flash Turbo below the midpoint.

Reka AI models average 77.0 on this benchmark. Reka Flash Turbo is 1.7 points below that provider line, so it is a weaker result than the average Reka AI model.

Among multimodal models, the average is 81.3. Reka Flash Turbo is 6.0 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 75.3 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 $10.19 per million input tokens, Reka Flash Turbo is above the median input price of $4.00 across the 600 models scored on MATH-500. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Command A Mini Cohere 8192 $8.12 71.0
ERNIE 4.5 Mini Baidu 32768 $8.62 71.0
GPT-4.1 Nano OpenAI 32768 $7.42 70.5
Grok 3 Mini xAI 200000 $9.67 73.9
Reka Flash Turbo Reka AI 128000 $10.19 75.1
Mistral Small 3 Chat Mistral AI 200000 $3.54 73.7
Gemini 3 Flash Nano Google DeepMind 32768 $7.56 69.4

Other benchmarks for Reka Flash Turbo

BenchmarkScoreRankPercentileRelative
MMLU-Pro 77.9 248 59th
GPQA Diamond 70.3 255 58th
SWE-bench Verified 63.3 248 59th
HumanEval 77.7 296 51th
AIME 2025 72.9 206 66th
LiveCodeBench 67.2 244 59th
IFEval 84.3 208 65th
TruthfulQA 78.3 247 59th
HellaSwag 86.5 195 68th
MMMU 72.2 238 60th
Arena Elo 1381.5 270 55th

FAQ

What score does Reka Flash Turbo get on MATH-500?

Reka Flash Turbo scores 75.3 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Reka Flash Turbo rank on MATH-500?

It ranks #321 of 600 models, in the 47th percentile. The leader is GPT-5.2 Max at 96.7.

Is Reka Flash Turbo good at MATH-500?

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 MATH-500 score calculated?

MATH-500 is a mathematics 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 Turbo cost?

Reka Flash Turbo costs $10.19 per million input tokens and $50.90 per million output tokens.

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