Benchmark scores
Higher is better for all benchmark scores (SWE-bench, GPQA, HLE, Terminal-Bench, etc.). Green marks the model with the higher score.
LLM Comparison
DeepSeek V4 Pro 0813 vs SWE-1.7: benchmark scores, pricing & comparison.
Side-by-side DeepSeek V4 Pro 0813 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 #17 vs #52AskClash overall scores 60.5 vs 21.0.
Pricing $0.43/$0.87 vs $0/$0Input and output token prices per 1M tokens when published.
Open Weight vs ProprietaryDeepSeek vs Cognition.
DeepSeek V4 Pro 0813 vs SWE-1.7 benchmark comparison
Green cells highlight the winning model for each metric. Scores are cached from the AskClash LLM leaderboard snapshot.
| Metric | DeepSeek V4 Pro 0813 | SWE-1.7 |
|---|---|---|
| Overall Score | 60.5 | 21.0 |
| Leaderboard Rank | #17 | #52 |
| RWT | 7.0 | 8.5 |
| HLE | 42.7 | — |
| GPQA | 90.1 | — |
| SWE-bench | 80.6 | — |
| SWE-Pro | 55.4 | — |
| Terminal-Bench | 87.9 | 81.5 |
| DeepSWE | 62.7 | — |
| MCP Atlas | 73.6 | — |
| Input Price (per 1M tokens) | $0.43 | $0 |
| Output Price (per 1M tokens) | $0.87 | $0 |
| Context Window | 1M | 256K |
| Benchmarks Published | 9 | 1 |
DeepSeek V4 Pro 0813 vs SWE-1.7 head-to-head charts
DeepSeek V4 Pro 0813 leads 2 and SWE-1.7 leads 1 of 3 shared benchmarks. SWE-1.7 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.
DeepSeek V4 Pro 0813SWE-1.7
Overall
RWT
Terminal-Bench
DeepSeek V4 Pro 0813
Input$0.43
Output$0.87
Workload$0.61
Context1M
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 DeepSeek V4 Pro 0813 and SWE-1.7 comparisons
Explore how DeepSeek V4 Pro 0813 and SWE-1.7 stack up against other top-ranked LLMs.
How to read this comparison
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.