CONTEXT BEATS MODEL: A CHEAP AGENT TOPS SWE-BENCH VERIFIED
A low-cost model paired with richer repo-aware context just topped SWE-bench Verified, showing agent wiring can outweigh model choice. A dev report shows MiniM...
A low-cost model paired with richer repo-aware context just topped SWE-bench Verified, showing agent wiring can outweigh model choice.
A dev report shows MiniMax M2.5 hit 78.2% on SWE-bench Verified after adding MCP-powered architectural context, edging past pricier models while staying cheap per run details. The gain came from better context, not a new model.
On the tougher SWE-Bench Pro board, results vary and are mostly self-reported leaderboard. Commentary also flags GPT-5.5 underperforming on Pro but shining in terminal-agent tasks, underscoring that benchmarks measure different skills explainer.
Agent architecture and context plumbing can deliver bigger gains than swapping to the most expensive model.
You can cut costs by pairing cheaper models with stronger repo-aware context, if your harness is solid.
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terminal
A/B: cheap model + MCP-fed repo context vs top-tier model with vanilla prompts on your real bug backlog; track PR acceptance and CI pass rate.
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terminal
Run SWE-bench-like multi-file fixes vs terminal-style tasks to see where your agent stack actually performs.
Legacy codebase integration strategies...
- 01.
Expose code search, dependency graph, and test runners via MCP servers; enforce read-only scopes and secret scrubbing.
- 02.
Keep agents out of prod writes: route fixes through PRs and full CI to quantify regression risk and real win rate.
Fresh architecture paradigms...
- 01.
Design for agents: strong test coverage, consistent issue templates, and a first-class indexing/context pipeline.
- 02.
Pick models on price/perf after the harness is stable; context quality first, model second.
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