Safety · Fireworks AI

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

Firesearch Max scores 71.7 on TruthfulQA, placing it #384 of 600 models in the index. The benchmark average is 73.6 and the leader is GPT-5.1 Max at 91.1.

Score
71.7
0–100 scale
Rank
#384
of 600
Percentile
36th
within the index
Benchmark avg
73.6
all models
Leader
91.1
GPT-5.1 Max
Gap to leader
19.4
points

Score distribution

The chart shows the top 10 models on TruthfulQA, with Firesearch Max 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 Max sits at #384 of 600. The leader, GPT-5.1 Max, scores 91.1, so the gap to the top is 19.4 points. The median model in this index scores 76.3, which puts Firesearch Max below the midpoint.

Fireworks AI models average 71.6 on this benchmark. Firesearch Max is 0.1 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 Max is 0.1 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 71.7 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 $7.80 per million input tokens, Firesearch Max 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
Reka Flash Mini Reka AI 16384 $5.77 65.5
Arctic Base Snowflake 32768 $2.27 67.5
Firesearch Reasoning Fireworks AI 32768 $7.74 69.0
Auto Turbo OpenRouter 65536 $7.96 70.9
Firesearch Max Fireworks AI 8192 $7.80 69.9
Claude Haiku 4.5 Nano Anthropic 8192 $6.47 68.7
DeepSeek-V3.2 8B DeepSeek 32768 $2.02 66.2

Other benchmarks for Firesearch Max

BenchmarkScoreRankPercentileRelative
MMLU-Pro 72.2 382 36th
GPQA Diamond 65.2 356 41th
SWE-bench Verified 61.0 297 51th
HumanEval 72.9 373 38th
MATH-500 73.0 358 40th
AIME 2025 62.5 370 38th
LiveCodeBench 63.7 327 46th
IFEval 78.0 368 39th
HellaSwag 81.1 366 39th
MMMU 67.3 355 41th
Arena Elo 1361.1 341 43th

FAQ

What score does Firesearch Max get on TruthfulQA?

Firesearch Max scores 71.7 on TruthfulQA in this index. The benchmark average is 73.6 and the top score is 91.1.

How does Firesearch Max rank on TruthfulQA?

It ranks #384 of 600 models, in the 36th percentile. The leader is GPT-5.1 Max at 91.1.

Is Firesearch Max 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 Max cost?

Firesearch Max costs $7.80 per million input tokens and $31.80 per million output tokens.

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