Instruction following · Fireworks AI

Firesearch Nano on IFEval: score, rank and what it means

Firesearch Nano scores 66.5 on IFEval, placing it #509 of 600 models in the index. The benchmark average is 78.6 and the leader is Claude Opus 4.5 Pro at 96.1.

Score
66.5
0–100 scale
Rank
#509
of 600
Percentile
15th
within the index
Benchmark avg
78.6
all models
Leader
96.1
Claude Opus 4.5 Pro
Gap to leader
29.6
points

Score distribution

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

Claude Opus 4.5 Pro 96.1
Claude Opus 4.5 Reasoning 95.9
GPT-5.2 Pro 95.6
GPT-5.2 Max 95.2
GPT-5.2 Reasoning 95.0
GPT-5.1 Pro 94.8
Gemini 3 Pro Max 94.7
GPT-5.1 Reasoning 94.6
Claude Opus 4.5 Max 94.5
o4 Reasoning 94.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
2 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
3 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
4 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
5 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
6 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
7 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9
8 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
9 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
10 o4 Reasoning OpenAI 1000000 $19.69 87.5

What this score means

On IFEval, Firesearch Nano sits at #509 of 600. The leader, Claude Opus 4.5 Pro, scores 96.1, so the gap to the top is 29.6 points. The median model in this index scores 81.2, which puts Firesearch Nano below the midpoint.

Fireworks AI models average 76.8 on this benchmark. Firesearch Nano is 10.3 points below that provider line, so it is a weaker result than the average Fireworks AI model.

Among mid-range models, the average is 76.5. Firesearch Nano is 10.0 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 66.5 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 $2.49 per million input tokens, Firesearch Nano is below the median input price of $4.00 across the 600 models scored on IFEval. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Yi-Large 8B 01.AI 32768 $0.88 56.1
DeepSeek-R1 1.5B DeepSeek 16384 $1.04 56.6
Mixtral Turbo 8B Together AI 4096 $0.75 54.1
Auto Nano OpenRouter 4096 $2.83 57.1
Firesearch Nano Fireworks AI 8192 $2.49 55.6
Fusion Nano OpenRouter 8192 $2.96 56.8
Llama 3 Modal 8B Modal 32768 $0.98 56.6

Other benchmarks for Firesearch Nano

BenchmarkScoreRankPercentileRelative
MMLU-Pro 63.0 488 19th
GPQA Diamond 52.6 493 18th
SWE-bench Verified 40.0 521 13th
HumanEval 58.9 513 15th
MATH-500 52.9 533 11th
AIME 2025 45.7 492 18th
LiveCodeBench 41.5 529 12th
TruthfulQA 62.6 495 18th
HellaSwag 73.2 475 21th
MMMU 54.8 500 17th
Arena Elo 1229.9 526 12th

FAQ

What score does Firesearch Nano get on IFEval?

Firesearch Nano scores 66.5 on IFEval in this index. The benchmark average is 78.6 and the top score is 96.1.

How does Firesearch Nano rank on IFEval?

It ranks #509 of 600 models, in the 15th percentile. The leader is Claude Opus 4.5 Pro at 96.1.

Is Firesearch Nano good at IFEval?

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 IFEval score calculated?

IFEval is a instruction following 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 Nano cost?

Firesearch Nano costs $2.49 per million input tokens and $11.16 per million output tokens.

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