Coding · Fireworks AI

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

Firesearch Reasoning scores 55.7 on SWE-bench Verified, placing it #378 of 600 models in the index. The benchmark average is 57.5 and the leader is GPT-5.2 Pro at 81.7.

Score
55.7
0–100 scale
Rank
#378
of 600
Percentile
37th
within the index
Benchmark avg
57.5
all models
Leader
81.7
GPT-5.2 Pro
Gap to leader
26.0
points

Score distribution

The chart shows the top 10 models on SWE-bench Verified, with Firesearch Reasoning 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, Firesearch Reasoning sits at #378 of 600. The leader, GPT-5.2 Pro, scores 81.7, so the gap to the top is 26.0 points. The median model in this index scores 61.0, which puts Firesearch Reasoning below the midpoint.

Fireworks AI models average 55.4 on this benchmark. Firesearch Reasoning is 0.3 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. Firesearch Reasoning is 0.8 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 55.7 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 $7.74 per million input tokens, Firesearch Reasoning 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
Arctic Base Snowflake 32768 $2.27 67.5
ERNIE 4.5 Nano Baidu 32768 $6.01 65.6
Phi-3.5 Instruct Microsoft 16384 $2.67 70.1
ERNIE 4.0 Mini Baidu 32768 $7.11 68.8
Firesearch Reasoning Fireworks AI 32768 $7.74 69.0
Gemini 3 Flash Nano Google DeepMind 32768 $7.56 69.4
Firesearch Fireworks AI 32768 $7.03 68.5

Other benchmarks for Firesearch Reasoning

BenchmarkScoreRankPercentileRelative
MMLU-Pro 72.3 381 37th
GPQA Diamond 63.1 382 36th
HumanEval 71.9 380 37th
MATH-500 70.9 380 37th
AIME 2025 62.8 367 39th
LiveCodeBench 63.9 321 47th
IFEval 77.3 376 37th
TruthfulQA 71.9 382 36th
HellaSwag 81.8 354 41th
MMMU 66.9 361 40th
Arena Elo 1364.8 332 45th

FAQ

What score does Firesearch Reasoning get on SWE-bench Verified?

Firesearch Reasoning scores 55.7 on SWE-bench Verified in this index. The benchmark average is 57.5 and the top score is 81.7.

How does Firesearch Reasoning rank on SWE-bench Verified?

It ranks #378 of 600 models, in the 37th percentile. The leader is GPT-5.2 Pro at 81.7.

Is Firesearch Reasoning 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 Firesearch Reasoning cost?

Firesearch Reasoning costs $7.74 per million input tokens and $33.47 per million output tokens.

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