Best AI models for coding
Coding in Nov 2026: judge by real bug fixes
The gold standard for coding picks is SWE-bench Verified — 500 real GitHub issues where the model must navigate a full repository, patch it and pass tests. It's far harder than "write me a snippet" and much closer to daily development. Recommendations below are tiered by budget and deployment constraints.
Last updated
Tiered picks
- Strongestlive-SWE-agent + Gemini 3 Pro Preview (2025-11-18)SWE-bench 77.4%
When budget allows and you want the best: complex refactors and stubborn bugs.
Official site ↗May require overseas network - BalancedMiniMax M2.5 (high)SWE-bench 75.8%
The daily driver: near-top ability with friendlier price and speed.
- Best valueGPT 5.2 (high)SWE-bench 72.8%
High-volume, cost-sensitive work: still 60%+ resolution at a fraction of flagship prices.
Official site ↗May require overseas network - Self-hostedClaude 4.5 Sonnet (high)SWE-bench 71.4%
Keep data in-house: open-weights models run your full loop behind your firewall.
Official site ↗May require overseas network
SWE-bench Verified resolution rate (top 15)
Verdict table
| Model | Resolved | Price tier | Verdict | Links |
|---|---|---|---|---|
| live-SWE-agent + Gemini 3 Pro Preview (2025-11-18) | 77.4% | Flagship | Top of the board: today's ceiling on real issues. | Source ↗AI Picks →May require overseas network |
| Claude 4.5 Opus (high) | 76.8% | Flagship | Stable board member with strong multi-turn fix rates. | Source ↗AI Picks →May require overseas network |
| Gemini 3 Flash (high) | 75.8% | Flagship | Stable board member with strong multi-turn fix rates. | Source ↗AI Picks →May require overseas network |
| MiniMax M2.5 (high) | 75.8% | Flagship | Stable board member with strong multi-turn fix rates. | Source ↗AI Picks → |
| Claude 4.6 Opus | 75.6% | Flagship | Stable board member with strong multi-turn fix rates. | Source ↗AI Picks →May require overseas network |
| Claude 4.5 Opus (20251101) (medium) | 74.4% | Flagship | Stable board member with strong multi-turn fix rates. | Source ↗AI Picks →May require overseas network |
SWE-bench VerifiedVersion 2026-02-26License MITSWE-bench Verified
A few terms first
FAQ
Which board should coders actually trust?
Real-repo resolution boards like SWE-bench Verified, not chat-preference boards. The hard parts of coding — reading existing code, multi-file edits, passing tests — only show up on real issue boards. This page's numbers come straight from the official submissions.
Why do "models" and "frameworks" always appear together?
Because top submissions are always "model + agent scaffold": the scaffold plans, retries and runs tests; the model reads and edits code. The same model can swing 10+ points across scaffolds. Watch the framework prefix in entry names (OpenHands, live-SWE-agent…).
How good are self-hosted open models now?
In 2026, open-weights Chinese models (DeepSeek, GLM, Qwen, Kimi…) reach the SWE-bench top twenty, some above 60% resolution — good enough for intranets, sensitive data and high-volume teams. The remaining gap is in very long context and cross-repository tasks.
What's left to improve after 80%?
Plenty. The remaining failures cluster in cross-repo dependencies, interactive debugging that needs a live environment, and long-context retrieval — which is why newer boards (SWE-bench Multimodal, Terminal-Bench) add those dimensions. Benchmark rotation is normal; we re-review our source mix yearly.
About the data
This column cites rather than reproduces: we quote only key scores and findings, each labeled with its source, version date and a link to the original — never a full-table copy of anyone's leaderboard.
Automated sources (LMArena / SWE-bench / LiveBench) sync weekly; the Artificial Analysis intelligence index and the pricing table are manually verified, with check dates noted in the changelog.
Benchmarks are not your experience. Each board measures something different and scores drift between releases — test against your own task before committing.
SWE-bench VerifiedVersion 2026-02-26License MITSWE-bench Verified
Written by the Flowerclaw editorial team · Reviewed by the Flowerclaw editorial team