Commonsense · Fireworks AI

Firesearch Pro on HellaSwag: score, rank and what it means

Firesearch Pro scores 81.2 on HellaSwag, placing it #362 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
81.2
0–100 scale
Rank
#362
of 600
Percentile
40th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
14.9
points

Score distribution

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

GPT-5.2 Max 96.1
GPT-5.2 Turbo 95.5
GPT-5.2 Pro 95.3
Claude Opus 4.5 Pro 95.2
Claude Sonnet 4.5 Reasoning 95.2
Grok 4 Reasoning 95.2
GPT-5.2 Vision 94.6
Gemini 3 Pro Turbo 94.6
GPT-5.1 Reasoning 94.4
o4 Pro 94.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
3 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
4 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
5 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4
8 Gemini 3 Pro Turbo Google DeepMind 400000 $19.62 86.4
9 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
10 o4 Pro OpenAI 1000000 $19.37 87.3

What this score means

On HellaSwag, Firesearch Pro sits at #362 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 14.9 points. The median model in this index scores 83.6, which puts Firesearch Pro below the midpoint.

Fireworks AI models average 80.3 on this benchmark. Firesearch Pro is 0.9 points above that provider line, so it is a stronger result than the average Fireworks AI model.

Among mid-range models, the average is 79.8. Firesearch Pro is 1.4 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 81.2 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 $7.67 per million input tokens, Firesearch Pro is above the median input price of $4.00 across the 600 models scored on HellaSwag. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Gemma 3 Base Google DeepMind 65536 $3.09 71.1
OLMo 2 Base Allen Institute for AI 65536 $2.39 67.4
o3 Nano OpenAI 32768 $7.78 70.6
Claude Haiku 4.5 Mini Anthropic 16384 $8.76 71.6
Firesearch Pro Fireworks AI 32768 $7.67 70.4
o4 Nano OpenAI 65536 $8.61 72.0
Auto OpenRouter 32768 $7.53 70.2

Other benchmarks for Firesearch Pro

BenchmarkScoreRankPercentileRelative
MMLU-Pro 72.6 370 38th
GPQA Diamond 68.4 305 49th
SWE-bench Verified 59.8 330 45th
HumanEval 75.3 338 44th
MATH-500 70.2 384 36th
AIME 2025 61.0 382 36th
LiveCodeBench 63.9 320 47th
IFEval 80.1 331 45th
TruthfulQA 72.8 371 38th
MMMU 68.7 330 45th
Arena Elo 1362.0 340 43th

FAQ

What score does Firesearch Pro get on HellaSwag?

Firesearch Pro scores 81.2 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does Firesearch Pro rank on HellaSwag?

It ranks #362 of 600 models, in the 40th percentile. The leader is GPT-5.2 Max at 96.1.

Is Firesearch Pro good at HellaSwag?

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 HellaSwag score calculated?

HellaSwag is a commonsense 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 Pro cost?

Firesearch Pro costs $7.67 per million input tokens and $32.83 per million output tokens.

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