Commonsense · Fireworks AI

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

Firesearch Turbo scores 79.8 on HellaSwag, placing it #380 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
79.8
0–100 scale
Rank
#380
of 600
Percentile
37th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
16.3
points

Score distribution

The chart shows the top 10 models on HellaSwag, with Firesearch Turbo 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 Turbo sits at #380 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 16.3 points. The median model in this index scores 83.6, which puts Firesearch Turbo below the midpoint.

Fireworks AI models average 80.3 on this benchmark. Firesearch Turbo is 0.5 points below that provider line, so it is a weaker result than the average Fireworks AI model.

Among mid-range models, the average is 79.8. Firesearch Turbo is 0.0 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 79.8 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 $7.58 per million input tokens, Firesearch Turbo 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
Sonar Pro Mini Perplexity 8192 $8.02 70.3
Arctic Snowflake 8192 $2.72 68.8
Claude Haiku 4.5 Nano Anthropic 8192 $6.47 68.7
Arctic Base Snowflake 32768 $2.27 67.5
Firesearch Turbo Fireworks AI 16384 $7.58 69.3
Grok 3 Nano xAI 8192 $7.12 67.8
Nemotron Nano Chat NVIDIA 32768 $2.21 66.2

Other benchmarks for Firesearch Turbo

BenchmarkScoreRankPercentileRelative
MMLU-Pro 74.2 347 42th
GPQA Diamond 64.4 372 38th
SWE-bench Verified 57.6 362 40th
HumanEval 73.6 366 39th
MATH-500 74.9 326 46th
AIME 2025 61.3 380 37th
LiveCodeBench 62.0 348 42th
IFEval 77.4 374 38th
TruthfulQA 72.6 374 38th
MMMU 64.0 389 35th
Arena Elo 1352.1 361 40th

FAQ

What score does Firesearch Turbo get on HellaSwag?

Firesearch Turbo scores 79.8 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does Firesearch Turbo rank on HellaSwag?

It ranks #380 of 600 models, in the 37th percentile. The leader is GPT-5.2 Max at 96.1.

Is Firesearch Turbo 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 Turbo cost?

Firesearch Turbo costs $7.58 per million input tokens and $33.44 per million output tokens.

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