The Ultimate GitHub Copilot Model Guide (2026): Every Model Compared by Cost, Context, and SWE-bench Accuracy
April 16, 2026 · 3 min read · Raymond
| Model Name | Context Window | SWE-bench (Verified) | Multiplier | Recommended Use Case |
|---|---|---|---|---|
| Claude Haiku 4.5 | 160K | 73.3% | 0.33x | Snappy, low-cost refactoring. |
| Claude Opus 4.5 | 160K | 80.9% | 3x | High-level architectural planning. |
| Claude Opus 4.6 | 192K | 80.8% | 3x | The "Big Brain" for logic-heavy debugging. |
| Claude Sonnet 4 | 144K | ~61.0% | 1x | Deprecating 2026-05-01. Move to 4.6. |
| Claude Sonnet 4.5 | 160K | 71.3% | 1x | Stable, reliable coding logic. |
| Claude Sonnet 4.6 | 160K | 75.2% | 1x | The current balanced favorite. |
| Gemini 2.5 Pro | 173K | ~61.2% | 1x | Reliable legacy multimodal tasks. |
| Gemini 3 Flash (Preview) | 173K | 75.4% | 0.33x | Fast responses for simple UI tweaks. |
| Gemini 3.1 Pro (Preview) | 173K | 75.6% | 1x | Strong reasoning with Google’s ecosystem. |
| GPT-4.1 | 128K | ~48.0% | 0x | Solid "Free" tier for legacy maintenance. |
| GPT-4o | 68K | 33.0% | 0x | Fast, unlimited, but lowest coding accuracy. |
| GPT-5 mini | 192K | 64.7% | 0x | Best All-Rounder: Unlimited & high context. |
| GPT-5.2 | 192K | 73.8% | 1x | Standard flagship performance. |
| GPT-5.2-Codex | 400K | 72.8% | 1x | Huge context for specialized code tasks. |
| GPT-5.3-Codex | 400K | 74.8% | 1x | Top-tier codebase-wide analysis. |
| GPT-5.4 | 400K | 76.9% | 1x | Current state-of-the-art for OpenAI. |
| GPT-5.4 mini | 400K | ~72.5% | 0.33x | The budget king for massive context. |
| Grok Code Fast 1 | 173K | 73.5% | 0.25x | Lightening fast; great for simple scripts. |
| Raptor mini (Preview) | 264K | ~65.0% | 0x | The MVP: Best free context/performance ratio. |
What the Benchmarks Actually Tell Us:
The 80% Ceiling: Breaking 80% on SWE-bench Verified (like Claude Opus 4.6 and 4.5 do) means the model isn't just autocompleting; it's acting as a highly autonomous agent capable of resolving complex cross-file dependencies. This justifies their heavy 3x multiplier cost.
The "Mini" Revolution: Models like GPT-5 mini (64.7%) and Raptor mini (~65.0%) are scoring double what legacy models like GPT-4o (33%) did back in 2024. The fact that these are essentially "free" (0x multiplier) on paid plans fundamentally changes how we can use Copilot for daily tasks.
The Codex Advantage: While standard GPT-5.4 edges out the Codex versions in raw percentage points, the 400K context of the Codex models paired with custom scaffolding makes them incredibly potent for repo-wide refactoring that standard models fail to hold in memory.