Coding · Fireworks AI

Firefunction on SWE-bench Verified: score, rank and what it means

Firefunction scores 60.6 on SWE-bench Verified, placing it #314 of 600 models in the index. The benchmark average is 57.5 and the leader is GPT-5.2 Pro at 81.7.

Score
60.6
0–100 scale
Rank
#314
of 600
Percentile
48th
within the index
Benchmark avg
57.5
all models
Leader
81.7
GPT-5.2 Pro
Gap to leader
21.1
points

Score distribution

The chart shows the top 10 models on SWE-bench Verified, with Firefunction highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 81.7
Claude Opus 4.5 Pro 81.1
GPT-5.2 Max 80.5
Claude Sonnet 4.5 Max 80.2
GPT-5.2 80.2
GPT-5.1 Pro 80.1
o4 Max 79.8
Claude Sonnet 4.5 Reasoning 79.6
Claude Opus 4.5 Max 79.5
Claude Opus 4.5 Reasoning 79.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
3 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
4 Claude Sonnet 4.5 Max Anthropic 1000000 $19.90 87.2
5 GPT-5.2 OpenAI 2000000 $19.71 88.0
6 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
7 o4 Max OpenAI 2000000 $19.51 86.2
8 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
9 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
10 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2

What this score means

On SWE-bench Verified, Firefunction sits at #314 of 600. The leader, GPT-5.2 Pro, scores 81.7, so the gap to the top is 21.1 points. The median model in this index scores 61.0, which puts Firefunction below the midpoint.

Fireworks AI models average 55.4 on this benchmark. Firefunction is 5.2 points above that provider line, so it is a stronger result than the average Fireworks AI model.

Among mid-range models, the average is 54.9. Firefunction is 5.7 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 60.6 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 SWE-bench Verified. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Command R+ Base Cohere 65536 $3.24 71.6
Hunyuan-Large Base Tencent 200000 $3.64 74.0
Nemotron 4 Base NVIDIA 8192 $3.29 73.0
Claude 3.7 Sonnet Mini Anthropic 32768 $9.74 73.0
Firefunction Fireworks AI 16384 $8.16 72.3
Gemma 3 Base Google DeepMind 65536 $3.09 71.1
Auto Pro OpenRouter 8192 $8.41 71.2

Other benchmarks for Firefunction

BenchmarkScoreRankPercentileRelative
MMLU-Pro 76.0 306 49th
GPQA Diamond 69.2 288 52th
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
HellaSwag 84.0 281 53th
MMMU 70.8 277 54th
Arena Elo 1356.8 349 42th

FAQ

What score does Firefunction get on SWE-bench Verified?

Firefunction scores 60.6 on SWE-bench Verified in this index. The benchmark average is 57.5 and the top score is 81.7.

How does Firefunction rank on SWE-bench Verified?

It ranks #314 of 600 models, in the 48th percentile. The leader is GPT-5.2 Pro at 81.7.

Is Firefunction good at SWE-bench Verified?

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 SWE-bench Verified score calculated?

SWE-bench Verified is a coding 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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