DeepSeek V4.1 Flash
DeepSeek's 552B parameter MIT-licensed Mixture-of-Experts model with a 1M-token context, updated October 17 with stronger agentic coding scores, and the top open-weight model on the Vals Index.
Model Story
DeepSeek released V4.1 Flash on September 10, 2026, under the MIT license, with weights on Hugging Face and ModelScope. It is a 552B total parameter Mixture-of-Experts model that activates only 16B parameters per token at decode (8B at prefill), with a 1M-token context window. That combination of a large knowledge base and a very small active footprint is what makes it a strong fit for on-premises hardware.
On October 17, 2026, DeepSeek shipped an update, V4.1-Flash-1017. On DeepSeek's own figures it lifted DeepSWE v1.1 from 74.2 to 77.0 and Terminal-Bench 4.0 from 31.2 to 42.3. DeepSeek reported that the September version already edged GPT-5.6 Sol (73.0) and Claude Opus 5 (74.0) on DeepSWE v1.1 while trailing both on Terminal-Bench 4.0 (31.2 against 39.9 and 51.8). The 1017 update closes much of that Terminal-Bench gap.
Independent results back it up: Vals.ai ranks DeepSeek V4.1 Flash the top open-weight model on its Vals Index. DeepSeek has not shipped a V4.1 Pro yet, so DeepSeek V4 Pro remains the larger option (see our DeepSeek V4 guide).
For Faraday Machines customers, V4.1 Flash is our pick for agentic coding and long-context work, and it ships on the three-unit Scale tier.
Key Specifications
| Developer | DeepSeek |
|---|---|
| Release Date | September 10, 2026 |
| Latest Update | V4.1-Flash-1017 (October 17, 2026) |
| Architecture | Sparse Mixture-of-Experts (MoE) |
| Total Parameters | 552 billion |
| Active Parameters | 16 billion at decode (8 billion at prefill) |
| Context Window | 1M tokens |
| License | MIT (full commercial freedom) |
| Weights | Hugging Face and ModelScope |
| Size at 4-bit | Roughly 300 GB |
| Faraday Fit | Scale (3 Mac Studios, 384GB) |
API Pricing
DeepSeek API rate card as of October 2026. Cache-hit input costs $0.006 per 1M tokens at peak. Off-peak rates drop to $0.15 input / $0.60 output, with cache hits at $0.003. DeepSeek's own API is inexpensive, so the case for running V4.1 Flash on-premises is less about the per-token rate and more about keeping data in-house, avoiding a foreign API for sensitive work, and a fixed cost that doesn't grow with usage.
Benchmarks
DeepSWE and Terminal-Bench scores are vendor-reported by DeepSeek. On those same figures, the 1017 Terminal-Bench 4.0 score of 42.3 now sits above the 39.9 DeepSeek listed for GPT-5.6 Sol, though still below Claude Opus 5's 51.8. The Vals Index result is independent.
On-Premises Deployment
DeepSeek V4.1 Flash fits Faraday's Scale tier. At 4-bit quantization its weights are roughly 300 GB, which fits within the 384GB of unified memory on three Mac Studios with headroom for working memory. Very long prompts use more memory, so how much of the 1M-token window you use in practice depends on your configuration and concurrency; Faraday sizes this with you.
Because only 16B parameters are active per token at decode, V4.1 Flash does far less compute per token than its 552B size suggests. Combined with the MIT license, that makes it Faraday's default for agentic coding and long-context work. Teams on the two-unit Growth tier should look at GLM-5.3-Flash instead.
Frequently Asked Questions
Can a small business run DeepSeek V4.1 Flash on-premises?
Yes. DeepSeek V4.1 Flash runs on Faraday Machines' Scale tier: three Mac Studios with 384GB of unified memory for $29,999 US one-time. At 4-bit quantization its 552B-parameter weights need roughly 300 GB, leaving headroom for working memory. Only 16B parameters are active per token at decode, so it does far less compute per token than its size suggests.
How much does DeepSeek V4.1 Flash cost?
DeepSeek's API rate card lists DeepSeek V4.1 Flash at $0.30 per 1M input tokens and $1.20 per 1M output tokens at peak, falling to $0.15 and $0.60 off-peak, with cache hits from $0.003 per 1M tokens, as of October 2026. Because the API is inexpensive, the case for running it on-premises with Faraday Machines is mainly keeping data in-house and a fixed cost that doesn't grow with usage.
What license does DeepSeek V4.1 Flash use?
DeepSeek V4.1 Flash is released under the MIT license, with weights on Hugging Face and ModelScope, which gives full commercial freedom. That sets it apart from Kimi K3 and the full GLM-5.3, which moved to custom licenses. The MIT license, together with its small 16B active footprint, is why Faraday Machines makes it the default model for agentic coding and long-context work.
How does DeepSeek V4.1 Flash compare to GPT-5.6 Sol and Claude Opus 5?
DeepSeek V4.1 Flash is competitive with both on DeepSeek's own coding figures. The October 17 update scores 77.0 on DeepSWE v1.1 and 42.3 on Terminal-Bench 4.0, above the 39.9 DeepSeek lists for GPT-5.6 Sol but below Claude Opus 5's 51.8. Independently, Vals.ai ranks DeepSeek V4.1 Flash the top open-weight model on its Vals Index, at 57.86% and 15th of 56 overall.
References
[1] VentureBeat. (2026). "DeepSeek V4.1 Flash debuts with $0.003/1M off-peak cached input rate and benchmarks eclipsing GPT-5.6 Sol, Claude Opus 5." September 2026. Available at: venturebeat.com
[2] NVIDIA. (2026). "deepseek-v4.1-flash" model card. Available at: build.nvidia.com
[3] Artificial Analysis. (2026). "DeepSeek V4.1 Flash" model page. Available at: artificialanalysis.ai
[4] Flowtivity. (2026). "DeepSeek V4.1 Flash benchmarks" (Vals Index results). Available at: flowtivity.ai
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