Microsoft's new MAI Code 1.1 Flash gets crushed by Deepseek on both price and performance
Microsoft has released MAI Code 1.1 Flash, a code model for GitHub Copilot. It's hard to see the point of Microsoft's MAI models when they trail OpenWeight alternatives on both price and performance, the same models Microsoft keeps saying it's a massive fan of.
Microsoft says the new model writes better code, is 25 percent more token-efficient, and costs a quarter of its June predecessor. Developers accepted 4 percent more of its output. Training involved "hundreds of thousands of reinforcement-learning environments in GitHub Copilot." In benchmarks, it edges past its predecessor and mini-models from Anthropic and OpenAI but gets crushed by Deepseek-V4-Flash-0731.
| Benchmark | MAI-Code-1.1-Flash | MAI-Code-1-Flash | Haiku 4.5 | GPT-5.4 mini | DeepSeek-V4-Flash-0731 |
|---|---|---|---|---|---|
| SWE-bench Verified | 72.6% | 71.6% | 69.8% | 69.2% | Not published |
| Terminal Bench 2.1 | 62.9% | 51.7% | 49.4% | 60.7% | 82.7% |
Cheaper than before, still pricier than Deepseek
MAI-Code-1.1-Flash looks like a budget model on paper, but it trails the more capable Deepseek on both price and performance. Cost per token doesn't tell the whole story without factoring in usage efficiency, but the gap in Deepseek's favor is likely significant either way.
That might explain why Microsoft buries the benchmark results in the model card and only touts vague improvement metrics ("code survival rose 4% and return visits increased 9%") over its predecessor in the official announcement, skipping any direct comparisons.
| Model | Input | Input with Cache | Output |
|---|---|---|---|
| DeepSeek-V4-Flash | $0.14 | $0.0028 | $0.28 |
| MAI Code 1.1 Flash | $0.20 | $0.02 | $1.20 |
| Claude Haiku 4.5 | $1.00 | $0.10 | $5.00 |
Microsoft's open AI talk doesn't match its model strategy
None of this squares with Microsoft's recent push to paint itself as an open AI champion. Instead of tapping more capable, freely available alternatives like Deepseek-V4-Flash, the company is sinking resources into a weaker, pricier in-house model that's proprietary and likely won't get an open-weights release.
The reason is probably the same one behind Microsoft's recent Copilot shakeup, where it swapped out OpenAI and Anthropic models for its own cheaper MAI alternatives to cut costs. The trade-off was worse performance for better margins.
MAI-Code-1.1-Flash fits the same pattern: Customers in the Microsoft ecosystem can still pick from different models depending on the app and use case, but Microsoft will almost certainly make its own models the default eventually. That alone would lock up a massive share of the market, since most users never actively choose a specific AI model anyway.
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