Coding · Fireworks AI

Firesearch Mini on LiveCodeBench: score, rank and what it means

Firesearch Mini scores 50.9 on LiveCodeBench, placing it #440 of 600 models in the index. The benchmark average is 61.0 and the leader is Claude Sonnet 4.5 Reasoning at 85.1.

Score
50.9
0–100 scale
Rank
#440
of 600
Percentile
27th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
34.2
points

Score distribution

The chart shows the top 10 models on LiveCodeBench, with Firesearch Mini highlighted. Longer bars mean higher scores.

Claude Sonnet 4.5 Reasoning 85.1
Grok 4 Reasoning 85.1
Claude Opus 4.5 85.0
GPT-5.2 Max 84.8
Grok 4 Turbo 84.7
GPT-5.1 Turbo 84.6
GPT-5.2 Pro 84.6
GPT-5.2 Reasoning 84.6
Claude Opus 4.5 Pro 84.1
Gemini 3 Pro Max 83.6

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
2 Grok 4 Reasoning xAI 2000000 $19.67 87.8
3 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
4 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
5 Grok 4 Turbo xAI 1000000 $19.21 86.7
6 GPT-5.1 Turbo OpenAI 2000000 $19.19 86.1
7 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
8 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
9 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
10 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9

What this score means

On LiveCodeBench, Firesearch Mini sits at #440 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 34.2 points. The median model in this index scores 64.7, which puts Firesearch Mini below the midpoint.

Fireworks AI models average 58.6 on this benchmark. Firesearch Mini is 7.7 points below that provider line, so it is a weaker result than the average Fireworks AI model.

Among mid-range models, the average is 58.3. Firesearch Mini is 7.4 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 50.9 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 $3.94 per million input tokens, Firesearch Mini is below the median input price of $4.00 across the 600 models scored on LiveCodeBench. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Magistral 7B Mistral AI 32768 $1.22 58.9
Llama 4 Maverick 8B Meta AI 4096 $1.64 63.4
Zephyr Chat Hugging Face 4096 $1.49 61.3
Hunyuan-Turbo Nano Tencent 32768 $4.65 62.7
Firesearch Mini Fireworks AI 32768 $3.94 61.5
Reka Flash Nano Reka AI 16384 $3.93 61.0
Llama 3.1 Turbo 8B Together AI 32768 $1.16 58.8

Other benchmarks for Firesearch Mini

BenchmarkScoreRankPercentileRelative
MMLU-Pro 67.5 424 29th
GPQA Diamond 55.7 452 25th
SWE-bench Verified 48.8 432 28th
HumanEval 65.5 435 28th
MATH-500 59.6 471 22th
AIME 2025 50.8 453 25th
IFEval 72.8 420 30th
TruthfulQA 66.5 436 27th
HellaSwag 77.2 412 31th
MMMU 61.1 419 30th
Arena Elo 1280.3 445 26th

FAQ

What score does Firesearch Mini get on LiveCodeBench?

Firesearch Mini scores 50.9 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does Firesearch Mini rank on LiveCodeBench?

It ranks #440 of 600 models, in the 27th percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is Firesearch Mini good at LiveCodeBench?

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 LiveCodeBench score calculated?

LiveCodeBench is a coding 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 Firesearch Mini cost?

Firesearch Mini costs $3.94 per million input tokens and $16.76 per million output tokens.

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