Safety · Fireworks AI

Firesearch on TruthfulQA: score, rank and what it means

Firesearch scores 75.1 on TruthfulQA, placing it #328 of 600 models in the index. The benchmark average is 73.6 and the leader is GPT-5.1 Max at 91.1.

Score
75.1
0–100 scale
Rank
#328
of 600
Percentile
45th
within the index
Benchmark avg
73.6
all models
Leader
91.1
GPT-5.1 Max
Gap to leader
16.0
points

Score distribution

The chart shows the top 10 models on TruthfulQA, with Firesearch 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 sits at #328 of 600. The leader, GPT-5.1 Max, scores 91.1, so the gap to the top is 16.0 points. The median model in this index scores 76.3, which puts Firesearch below the midpoint.

Fireworks AI models average 71.6 on this benchmark. Firesearch is 3.5 points above that provider line, so it is a stronger result than the average Fireworks AI model.

Among mid-range models, the average is 71.6. Firesearch is 3.5 points above that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 75.1 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 $7.03 per million input tokens, Firesearch is above 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
o3 Nano OpenAI 32768 $7.78 70.6
GPT-4.1 Nano OpenAI 32768 $7.42 70.5
Phi-3.5 Instruct Microsoft 16384 $2.67 70.1
o4 Nano OpenAI 65536 $8.61 72.0
Firesearch Fireworks AI 32768 $7.03 68.5
Llama 3.1 Cerebras Base Cerebras 65536 $3.36 72.7
Nova Lite Max Amazon 200000 $9.79 73.4

Other benchmarks for Firesearch

BenchmarkScoreRankPercentileRelative
MMLU-Pro 71.6 384 36th
GPQA Diamond 65.0 359 40th
SWE-bench Verified 55.6 380 37th
HumanEval 73.6 365 39th
MATH-500 68.4 394 34th
AIME 2025 59.1 393 35th
LiveCodeBench 57.1 393 35th
IFEval 78.1 367 39th
HellaSwag 82.4 338 44th
MMMU 67.4 353 41th
Arena Elo 1353.2 358 40th

FAQ

What score does Firesearch get on TruthfulQA?

Firesearch scores 75.1 on TruthfulQA in this index. The benchmark average is 73.6 and the top score is 91.1.

How does Firesearch rank on TruthfulQA?

It ranks #328 of 600 models, in the 45th percentile. The leader is GPT-5.1 Max at 91.1.

Is Firesearch 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 cost?

Firesearch costs $7.03 per million input tokens and $29.81 per million output tokens.

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