Commonsense · Fireworks AI

Firefunction on HellaSwag: score, rank and what it means

Firefunction scores 84.0 on HellaSwag, placing it #281 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
84.0
0–100 scale
Rank
#281
of 600
Percentile
53th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
12.1
points

Score distribution

The chart shows the top 10 models on HellaSwag, with Firefunction 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, Firefunction sits at #281 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 12.1 points. The median model in this index scores 83.6, which puts Firefunction above the midpoint.

Fireworks AI models average 80.3 on this benchmark. Firefunction is 3.7 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. Firefunction is 4.2 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 84.0 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 $8.16 per million input tokens, Firefunction 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 Instruct Google DeepMind 128000 $3.72 74.1
Llama 3 Modal Modal 32768 $3.82 74.9
Llama 3 Modal Base Modal 16384 $3.21 72.2
OLMo 2 Instruct Allen Institute for AI 32768 $3.03 71.7
Firefunction Fireworks AI 16384 $8.16 72.3
Nova Lite Reasoning Amazon 32768 $9.92 74.3
Auto Turbo OpenRouter 65536 $7.96 70.9

Other benchmarks for Firefunction

BenchmarkScoreRankPercentileRelative
MMLU-Pro 76.0 306 49th
GPQA Diamond 69.2 288 52th
SWE-bench Verified 60.6 314 48th
HumanEval 75.1 342 43th
MATH-500 76.7 288 52th
AIME 2025 69.0 281 53th
LiveCodeBench 61.4 357 41th
IFEval 78.8 359 40th
TruthfulQA 73.6 362 40th
MMMU 70.8 277 54th
Arena Elo 1356.8 349 42th

FAQ

What score does Firefunction get on HellaSwag?

Firefunction scores 84.0 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does Firefunction rank on HellaSwag?

It ranks #281 of 600 models, in the 53rd percentile. The leader is GPT-5.2 Max at 96.1.

Is Firefunction good at HellaSwag?

Yes, relative to the index: it is above the median and inside the top half of scores. 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 Firefunction cost?

Firefunction costs $8.16 per million input tokens and $41.40 per million output tokens.

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