LLM Comparison

SWE-2 vs SWE-1.7: benchmark scores, pricing & comparison.

Side-by-side SWE-2 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.

Rank #24 vs #35AskClash overall scores 59.7 vs 54.0.
Pricing $0/$0 vs $0/$0Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryCognition vs Cognition.

SWE-2 vs SWE-1.7 benchmark comparison

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

MetricSWE-2SWE-1.7
Overall Score59.754.0
Leaderboard Rank#24#35
ACB60.0
RWT8.58.5
Terminal-Bench92.881.5
DeepSWE73.0
Input Price (per 1M tokens)$0$0
Output Price (per 1M tokens)$0$0
Context Window256K256K
Benchmarks Published31

SWE-2 vs SWE-1.7 head-to-head charts

SWE-2 leads 2 and SWE-1.7 leads 0 of 3 shared benchmarks. Charts show only benchmarks both models publish.

SWE-2SWE-1.7
Overall
59.7SWE-2
54.0SWE-1.7
RWT
8.5SWE-2
8.5SWE-1.7
Terminal-Bench
92.8SWE-2
81.5SWE-1.7
SWE-2
Input$0
Output$0
Workload$0.00
Context256K
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 SWE-2 and SWE-1.7 comparisons

Explore how SWE-2 and SWE-1.7 stack up against other top-ranked LLMs.

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.