DeepSeek V4: The Most Versatile Model You Can Run
Cheaper than GPT-5.5, versatile across tasks, and fully sovereign
Key takeaways
- DeepSeek released V4.1 Flash on September 10, 2026: an MIT-licensed model with a 552B-parameter backbone plus a ~196B-parameter Engram memory, 16B active at decode and a 1M-token context. V4 Pro remains its Pro option.
- DeepSeek’s rate card lists V4.1 Flash at $0.30 input and $1.20 output per 1M tokens at peak, roughly 33–42× less per token than GPT-6 Astra’s $10 / $50.
- DeepSeek reports its October 17 V4.1-Flash-1017 update scores 77.0 on DeepSWE v1.1, and Vals.ai ranks V4.1 Flash the top open-weight model on the Vals Index (57.86%).
- DeepSeek’s hosted API routes data to servers in China subject to the National Intelligence Law; Western hosts keep data local but still send it to a third party.
- DeepSeek V4.1 Flash is about 510GB as released and about 400–445GB at 4-bit, so Faraday Machines runs it on-premises on its Scale plan (one 512GB Mac Studio, $999 US a month) as a 1- to 3-bit build, or at 4-bit on a larger setup.
October 2026 update
DeepSeek has since shipped DeepSeek V4.1 Flash (September 10, 2026), followed by the V4.1-Flash-1017 update on October 17. V4.1 Pro has not shipped yet, so V4 Pro remains DeepSeek’s Pro option.
- Specs: 552B-parameter backbone plus a ~196B-parameter Engram memory, 16B active at decode, 1M-token context, MIT license, weights on Hugging Face and ModelScope.
- Pricing (DeepSeek rate card): $0.30 input / $1.20 output per 1M tokens at peak, $0.15 / $0.60 off-peak, with cache hits as low as $0.003. GPT-6 Astra lists at $10 / $50 — roughly 33–42× more per token.
- Benchmarks: DeepSeek reports the 1017 update lifting DeepSWE v1.1 from 74.2 to 77.0 and Terminal-Bench 4.0 from 31.2 to 42.3. Independently, Vals.ai ranks it the top open-weight model on the Vals Index (57.86%).
- On Faraday: it runs on the Faraday Scale plan’s single 512GB Mac Studio as a 1- to 3-bit build of about 250–350GB, such as Unsloth’s 1-bit build (about 250GB). Lower-bit builds trade some quality, most noticeably on long or precise work. A 4-bit build (about 400–445GB) needs a larger setup.
- Size correction (October 19): we previously listed V4.1 Flash at roughly 300GB at 4-bit. That was wrong: its separate Engram memory and FP8 weights make it about 510GB as released.
Two Models, One MIT License
DeepSeek V4 launched April 24, 2026 in two variants: Flash for speed and throughput, Pro for peak reasoning. Both ship under the MIT license — no usage restrictions, no commercial limits, no vendor permission required.
Versatility Across Tasks
Coding and Engineering
V4 Flash Max scores 91.6% on LiveCodeBench. Pro Max hits 93.5%. Codeforces ratings of 3052 (Flash) and 3206 (Pro) place both in expert territory. From code reviews to greenfield development, these models deliver.
Reasoning and Research
Pro Max hits 90.1% on GPQA Diamond (graduate-level science) and 37.7% on HLE (humanity's last exam). Flash Max reaches 88.1% on GPQA Diamond. Three thinking modes — non-think, think high, think max — let you trade speed for depth.
Agentic Workflows
V4 Pro Max scores 67.9% on Terminal Bench 2.0 and 55.4% on SWE-bench Pro. Flash Max handles 56.9% on Terminal Bench. For tool use, multi-step planning, and autonomous workflows, both variants are production-ready.
Long-Context Processing
1M-token context windows on both models handle entire codebases, full document sets, and extended conversations without chunking. The hybrid attention architecture (CSA + HCA) reduces KV cache memory by 90% versus prior models.
The Data Sovereignty Spectrum
Open-source means you choose where inference happens. That choice has real consequences for your data.
DeepSeek Hosted API
Cheapest path, but data routes to servers in China subject to the National Intelligence Law. Chinese law can compel access to data processed on domestic servers. No data processing agreement overrides this.
Western Cloud Providers
Providers like Together AI and Fireworks host DeepSeek models on US or Canadian infrastructure. Data stays local, governed by that provider's jurisdiction and terms. A solid middle ground — but you still send data to a third party.
On-Premises with Faraday
Full data sovereignty. Inference runs on hardware you control, inside your network, behind your firewall. No third-party terms, no jurisdiction questions, no data processing agreements needed. Your data never leaves your control.
On-Premises vs Cloud
Cloud DeepSeek V4
- Per-token billing that scales with usage
- Data processed on third-party infrastructure
- DeepSeek API: data subject to China's National Intelligence Law
- Western providers: data stays local but leaves your network
- API availability depends on provider uptime
Faraday On-Premises
- $299 / $599 / $999 US a month — hardware + service for the full 36-month term
- Unlimited inference with zero per-token cost
- Data never leaves your office
- Run DeepSeek V4.1 Flash on Scale, or open models like GLM-5.3-Flash and Qwen3.8-27B on smaller tiers
- 100% uptime — no cloud dependency
Frequently Asked Questions
Can a small business run DeepSeek V4.1 Flash on-premises?
Yes. DeepSeek V4.1 Flash runs on the Faraday Machines Scale plan, a single Mac Studio with 512GB of unified memory, as a 1- to 3-bit build of about 250–350GB. It is larger than its 552B-parameter backbone suggests, because it also carries an Engram memory of about 196B parameters; it is about 510GB as released, so a 4-bit build (about 400–445GB) needs a larger setup. Lower-bit builds trade some quality, most noticeably on long or precise work. Scale costs $999 US a month over a 36-month term, including hardware, updates, maintenance and support. Smaller teams can start with a 1- to 2-bit build of GLM-5.3-Flash on Growth at $599 a month or Qwen3.8-27B on Starter at $299 a month.
Is it safe to use the DeepSeek API with business data?
It depends on the data. DeepSeek’s hosted API is the cheapest option, but data routes to servers in China, where the National Intelligence Law can compel access, and no data processing agreement overrides that. Western providers such as Together AI and Fireworks host DeepSeek models on US or Canadian infrastructure, but data still goes to a third party. Running DeepSeek on-premises keeps all data inside your network.
How much does the DeepSeek V4.1 Flash API cost?
DeepSeek’s rate card lists V4.1 Flash at $0.30 per 1M input tokens and $1.20 per 1M output tokens at peak, and $0.15 / $0.60 off-peak, with cache hits as low as $0.003. That is roughly 33–42× less per token than GPT-6 Astra at $10 / $50. On-premises, Faraday Machines replaces per-token billing with a fixed monthly plan, so inference has no per-token cost.
What license does DeepSeek V4 use?
DeepSeek V4 Flash, V4 Pro and V4.1 Flash are all released under the MIT license, which allows commercial use, modification and redistribution with no usage restrictions and no vendor permission required. V4.1 Flash weights are available on Hugging Face and ModelScope. The permissive license means businesses can run DeepSeek models on hardware they control, such as a Faraday Machines cluster, without negotiating terms with DeepSeek.
Is DeepSeek V4.1 Pro available yet?
Not yet. As of October 2026, DeepSeek has shipped V4.1 Flash (September 10, 2026) and its V4.1-Flash-1017 update (October 17), but V4.1 Pro has not been released, so DeepSeek V4 Pro remains the Pro option. V4 Pro launched on April 24, 2026 and, in its Max mode, scores 93.5% on LiveCodeBench and 55.4% on SWE-bench Pro.
References
[1] VentureBeat. (2026). "DeepSeek V4.1 Flash debuts with $0.003/1M off-peak cached input rate." 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." Available at: artificialanalysis.ai
[4] Flowtivity. (2026). "DeepSeek V4.1 Flash benchmarks." Available at: flowtivity.ai
[5] Morph. (2026). "OpenAI API pricing." Available at: morphllm.com
[6] Faraday Machines. (2026). "DeepSeek V4.1 Flash Model Profile." Available at: faradaymachines.com/models/deepseek-v4-1-flash
[7] DeepSeek. (2026). "DeepSeek-V4.1-Flash" model page (checkpoint sizes). Available at: huggingface.co
[8] modelfit.io. (2026). "DeepSeek V4.1 Flash Mac memory requirements." Available at: modelfit.io
[9] Unsloth. (2026). "DeepSeek-V4.1-Flash-1017-GGUF." Available at: huggingface.co
Run DeepSeek On Hardware You Control
MIT-licensed models, unlimited inference, full data sovereignty. Faraday Machines puts DeepSeek V4.1 Flash on your premises on a Scale plan’s 512GB Mac Studio, alongside open models like GLM-5.3-Flash and Qwen3.8-27B.
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