DeepSeek releases V4.1-Flash-1017 under MIT: DeepSWE v1.1 rises from 74.2 to 77.0 and Terminal-Bench 4.0 from 31.2 to 42.3
A minor update to V4.1-Flash with clear gains on coding and agent benchmarks, and DeepSeek says it also finishes faster with shorter outputs. How much it moved and where it sits next to closed models.
// Key points
- The repository and weights are MIT-licensed; DeepSeek says reasoning, coding, agent and vision benchmarks all improve while task time and output length go down.
- Its table: 77.0 on DeepSWE v1.1 (74.2 for the previous version, 74.0 for Opus 5, 73.0 for GPT-5.6 Sol) and 42.3 on Terminal-Bench 4.0 (31.2 before, 51.8 for Opus 5), the latter run in the Claude Code harness.
- Automation-Bench v1.0.6 goes from 54.8 to 60.5 and Apex Bench v1.1 from 64.6 to 72.1.
- The recommended context window is 1M with max_tokens of at least 256K; there is no Jinja chat template, only a Python reference encoder and the Rust-based deepseek-recipe libraries.
Builder's takePut it next to Beam on 10-17 and Muse Spark Open on 10-16 and open coding models closed in on closed ones all week. I'd point Claude Code at it on a batch of real tasks from my own repos, checking whether shorter outputs still mean complete changes; note the missing Jinja template before self-hosting, and don't force a generic one onto it.