Safety · Fireworks AI

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

Firesearch Nano scores 62.6 on TruthfulQA, placing it #495 of 600 models in the index. The benchmark average is 73.6 and the leader is GPT-5.1 Max at 91.1.

Score
62.6
0–100 scale
Rank
#495
of 600
Percentile
18th
within the index
Benchmark avg
73.6
all models
Leader
91.1
GPT-5.1 Max
Gap to leader
28.5
points

Score distribution

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

GPT-5.1 Max 91.1
Gemini 3 Pro Reasoning 90.3
GPT-5.1 Reasoning 90.0
GPT-5.2 Pro 90.0
GPT-5.2 89.7
Gemini 3 Pro Max 89.6
Grok 4 Reasoning 89.4
Qwen3-Max Max 89.3
GPT-5.1 89.2
GPT-5.1 Turbo 89.2

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
2 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
3 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
4 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
5 GPT-5.2 OpenAI 2000000 $19.71 88.0
6 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9
7 Grok 4 Reasoning xAI 2000000 $19.67 87.8
8 Qwen3-Max Max Alibaba Cloud 400000 $18.53 85.9
9 GPT-5.1 OpenAI 2000000 $19.01 86.0
10 GPT-5.1 Turbo OpenAI 2000000 $19.19 86.1

What this score means

On TruthfulQA, Firesearch Nano sits at #495 of 600. The leader, GPT-5.1 Max, scores 91.1, so the gap to the top is 28.5 points. The median model in this index scores 76.3, which puts Firesearch Nano below the midpoint.

Fireworks AI models average 71.6 on this benchmark. Firesearch Nano is 9.0 points below that provider line, so it is a weaker result than the average Fireworks AI model.

Among mid-range models, the average is 71.6. Firesearch Nano is 9.0 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 62.6 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 TruthfulQA. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Llama 3.1 Turbo 7B Together AI 8192 $0.98 56.4
MiniMax-M2 1.5B MiniMax 16384 $0.84 54.6
MiniMax-Text 7B MiniMax 16384 $1.10 57.7
Mistral Small 3 8B Mistral AI 8192 $0.99 57.2
Firesearch Nano Fireworks AI 8192 $2.49 55.6
Yi-Lightning 7B 01.AI 32768 $1.00 55.9
DeepSeek-Coder 8B DeepSeek 32768 $1.26 58.7

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
IFEval 66.5 509 15th
HellaSwag 73.2 475 21th
MMMU 54.8 500 17th
Arena Elo 1229.9 526 12th

FAQ

What score does Firesearch Nano get on TruthfulQA?

Firesearch Nano scores 62.6 on TruthfulQA in this index. The benchmark average is 73.6 and the top score is 91.1.

How does Firesearch Nano rank on TruthfulQA?

It ranks #495 of 600 models, in the 18th percentile. The leader is GPT-5.1 Max at 91.1.

Is Firesearch Nano good at TruthfulQA?

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 TruthfulQA score calculated?

TruthfulQA is a safety 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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