LLM Comparison

Qwen3.8 27B vs SWE-1.7: benchmark scores, pricing & comparison.

Side-by-side Qwen3.8 27B vs SWE-1.7 comparison across SWE-bench, GPQA, HLE, Terminal-Bench, coding agent scores, token pricing, context window, and AskClash RWT. Green marks the winner on each benchmark.

Open live leaderboardQwen3.8 27B model pageSWE-1.7 model page
Rank #17 vs #55AskClash overall scores 57.0 vs 20.0.
Pricing $0.45/$3.20 vs $0/$0Input and output token prices per 1M tokens when published.
Open Weight vs ProprietaryAlibaba vs Cognition.

Qwen3.8 27B vs SWE-1.7 benchmark comparison

Green cells highlight the winning model for each metric. Scores are cached from the AskClash LLM leaderboard snapshot.

MetricQwen3.8 27BSWE-1.7
Overall Score57.020.0
Leaderboard Rank#17#55
ACB56.4—
RWT—8.5
HLE30.8—
GPQA89.2—
IFEval79.5—
SWE-Pro61.7—
Terminal-Bench73.081.5
DeepSWE42.2—
OSWorld84.3—
CharXiv90.2—
Input Price (per 1M tokens)$0.45$0
Output Price (per 1M tokens)$3.20$0
Context Window262K256K
Benchmarks Published91

Qwen3.8 27B vs SWE-1.7 head-to-head charts

Qwen3.8 27B leads 1 and SWE-1.7 leads 1 of 2 shared benchmarks. SWE-1.7 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Qwen3.8 27BSWE-1.7
Overall
57.0Qwen3.8 27B
20.0SWE-1.7
Terminal-Bench
73.0Qwen3.8 27B
81.5SWE-1.7
Qwen3.8 27B
Input$0.45
Output$3.20
Workload$1.09
Context262K
SWE-1.7
Input$0
Output$0
Workload$0.00
Context256K

Workload = published cost of 1M input + 200K output tokens. Open the live leaderboard for interactive compare charts.

More Qwen3.8 27B and SWE-1.7 comparisons

Explore how Qwen3.8 27B and SWE-1.7 stack up against other top-ranked LLMs.

Claude Opus 5 vs Qwen3.8 27BClaude Opus 5 vs SWE-1.7Claude Fable 5 vs Qwen3.8 27BClaude Fable 5 vs SWE-1.7Grok 4.6 vs Qwen3.8 27BGrok 4.6 vs SWE-1.7GPT-5.6 Sol vs Qwen3.8 27BGPT-5.6 Sol vs SWE-1.7Kimi K3 vs Qwen3.8 27BKimi K3 vs SWE-1.7

How to read this comparison

Benchmark scores

Higher is better for all benchmark scores (SWE-bench, GPQA, HLE, Terminal-Bench, etc.). Green marks the model with the higher score.

Token pricing

Lower is better for input and output prices. Green marks the cheaper model per 1M tokens.

Coverage matters

Models with fewer disclosed benchmark cells may have inflated percentile scores. Check the benchmark cell count for context.

This comparison page is generated from the AskClash LLM leaderboard cache. Open the live leaderboard for real-time scores and interactive filtering.