DeepSeek Models Guide: V4 Pro vs V4.1 Flash Compared

DeepSeek’s current API lineup has 2 models, deepseek-flash (V4.1 Flash) for cheap, fast work and deepseek-v4-pro for harder reasoning, and both offer a 1M-token context window and ship their weights under the MIT license. Flash costs $0.30 per million cache-miss input tokens at peak hours, against $1.32 for Pro.

I read DeepSeek’s API pricing page, its Hugging Face model cards, and recent Reddit and Facebook discussion in October 2026. My pick: default to Flash for coding, agents, and image input, and move to Pro only when Flash fails your own tests.

For a head-to-head against a hosted rival, see our DeepSeek vs ChatGPT comparison.

How I Researched This Guide

Model names, context lengths, and prices come from DeepSeek’s official API documentation, and parameter counts and licenses come from the Hugging Face model cards, all checked in October 2026. Benchmark numbers are DeepSeek’s own and are labeled vendor-reported.

I did not benchmark the models myself. Community signals come from r/LocalLLaMA thread titles and Facebook posts collected with Apify, and Quora searches returned no usable results in my run.

Which DeepSeek Models Are Current in 2026?

DeepSeek lists 2 current API models: deepseek-flash, served by DeepSeek-V4.1-Flash-1017, and deepseek-v4-pro, served by DeepSeek-V4-Pro-0813. The table shows the specs DeepSeek publishes for each.

Field	deepseek-flash	deepseek-v4-pro
Model version	DeepSeek-V4.1-Flash-1017	DeepSeek-V4-Pro-0813
Parameters (Hugging Face listing)	763B	1.7T
Context length	1M tokens	1M tokens
Max output	384K tokens	384K tokens
Thinking mode	Non-thinking and thinking (default)	Non-thinking and thinking (default)
Vision input	Supported	Not supported
Concurrency limit	2,500	500
License	MIT	MIT

The older names deepseek-v4-flash and deepseek-v4-flash-vision-exp still work but are retired. Requests to them route to V4.1 Flash and bill at the Flash price.

What Is DeepSeek V4.1 Flash?

DeepSeek V4.1 Flash is the fast, low-cost model, listed at 763B parameters with a 1M-token context window, vision support, and an MIT license. The current checkpoint, 1017, improves reasoning, coding, agentic tasks, and visual benchmarks while shortening outputs to cut cost.

DeepSeek reports 77.0 on DeepSWE v1.1, 60.5 on Automation-Bench v1.0.6, and 42.3 on Terminal-Bench 4.0 for this checkpoint. Treat those as vendor-reported results from DeepSeek’s own evaluation setups.

Flash is the only DeepSeek model with image input. It also carries the higher concurrency limit of 2,500 requests, five times Pro’s 500.

What Is DeepSeek V4 Pro?

DeepSeek V4 Pro is the larger reasoning and agent model, listed at 1.7T parameters with a 1M-token context window and an MIT license. The 0813 release is the official version that supersedes the preview, with stronger agentic capabilities.

It offers 3 reasoning-effort levels, low, high, and max, and DeepSeek recommends a 384K maximum output for the high and max levels. It ships with a DSpark speculative decoding module and works with vLLM and SGLang for self-hosting.

Pro has no vision support. If your workflow sends screenshots or charts, Flash is the only DeepSeek option.

How Much Does the DeepSeek API Cost?

DeepSeek API prices run from $0.003 to $3.96 per million tokens, with off-peak rates at half the peak rates. The table lists DeepSeek’s published per-million-token prices.

Price per 1M tokens	Flash off-peak	Flash peak	Pro off-peak	Pro peak
Input, cache hit	$0.003	$0.006	$0.022	$0.044
Input, cache miss	$0.15	$0.30	$0.66	$1.32
Output	$0.60	$1.20	$1.98	$3.96

Peak hours run 01:00 to 04:00 and 06:00 to 10:00 UTC, Monday through Friday, excluding Chinese public holidays. Every other hour counts as off-peak, including weekends.

Search and Fetch calls cost $0.75 per 1,000 successful requests each. DeepSeek makes server-side calls through DeepSeek Harness, Claude Code, or Codex free until 00:00 Beijing time on November 1, 2026.

How Does DeepSeek Pricing Compare With Claude and Other Closed Models?

A workload of 10 million cache-miss input tokens and 2 million output tokens costs $5.40 on Flash and $21.12 on Pro at peak rates, against $80 on Claude Opus 5.5 at list price. Off-peak, the same workload costs $2.70 on Flash and $10.56 on Pro.

That makes Flash about 15 times cheaper than Opus 5.5 for this mix. Claude Opus 5.5 lists $4 input and $20 output per million tokens, as covered in our Anthropic Claude models guide.

Price is not quality. For a capability comparison, read our DeepSeek vs Claude article.

Which DeepSeek Model Should You Use?

Use Flash by default, Pro for hard reasoning and long agent runs, and neither when you need a vendor-hosted privacy guarantee you can audit yourself. The branches below tie each pick to a published spec.

Choose Flash if:
– You send images, since only Flash supports vision.
– You run high-volume calls, where its $0.30 peak input price and 2,500 concurrency matter.

Choose Pro if:
– You run difficult reasoning or long-horizon agents and accept $1.32 peak input pricing.
– You want the max reasoning-effort level for the hardest tasks.

Choose self-hosting if:
– You need data to stay on your own infrastructure, since both models carry MIT-licensed weights on Hugging Face.
– You accept the hardware cost of a 763B or 1.7T parameter model.

What Are DeepSeek R1 and V3, and Are They Still Current?

DeepSeek R1 and V3 are earlier-generation models that no longer appear in DeepSeek’s current API pricing table, which lists only deepseek-flash and deepseek-v4-pro. Their weights remain on Hugging Face under the deepseek-ai organization.

R1 targeted reasoning and V3 targeted general chat, and V4 merges both modes into one model with a thinking toggle. If an older tutorial tells you to call deepseek-reasoner, check DeepSeek’s documentation first, because third-party guides report those names stopped working after the V4 launch.

Pin the model name deepseek-flash or deepseek-v4-pro in new code.

What Do Reddit and Facebook Users Say About DeepSeek?

Community attention centers on V4.1 Flash’s coding scores and open weights. On r/LocalLLaMA, the Hugging Face release thread drew 1,121 upvotes and 317 comments, and “DeepSeek V4.1 Flash (1017) Now Leads Open-Weight Models” drew 789 upvotes and 165 comments.

Facebook posts returned by my search repeat DeepSeek’s launch claims:
– The 77% DeepSWE v1.1 score and the MIT license.
– The new Search and Fetch APIs at $0.75 per 1,000 requests.
– DeepSeek Harness, a desktop agent that edits local files.

Most of those posts are news reposts with near-zero engagement, so treat them as announcements, not independent testing. One post reports DeepSeek open-sourced an inference engine called DeepInfer, but its own author notes the project lacks reproducible benchmarks.

Frequently Asked Questions (FAQ)

What is the newest DeepSeek model?

DeepSeek-V4.1-Flash-1017 is the newest checkpoint, served as deepseek-flash. DeepSeek-V4-Pro-0813 is the larger companion model.

Is DeepSeek free to use?

DeepSeek’s app is free to chat with, and the API is pay-as-you-go. Flash costs as little as $0.003 per million cache-hit input tokens off-peak.

Is DeepSeek open source?

The weights for V4.1 Flash and V4 Pro are released under the MIT license on Hugging Face, which permits commercial use.

What is the difference between DeepSeek V4 Pro and V4.1 Flash?

Pro is larger (1.7T parameters), costs 4.4 times more per cache-miss input token, and targets hard reasoning, while Flash (763B) adds vision at a lower price. Both offer a 1M-token context window.

How big is the DeepSeek context window?

Both current models support 1M tokens of context and up to 384K tokens of output.

Is DeepSeek better than ChatGPT?

DeepSeek costs far less per token, while ChatGPT offers a broader consumer product with plans from Free to Pro. Compare them directly in our DeepSeek vs ChatGPT article.

Where can I find DeepSeek alternatives?

Browse our DeepSeek Alternatives roundup for models with similar pricing and open weights.

Final Verdict

DeepSeek V4.1 Flash is the best value open-weight model for coding and agents, DeepSeek V4 Pro is the upgrade for hard reasoning, and the MIT license makes both strong self-hosting candidates. Flash at $0.30 per million input tokens undercuts closed flagship models by an order of magnitude.

Confirm prices on DeepSeek’s pricing page before you budget, since peak and off-peak rates apply and DeepSeek updates the lineup often. For the bigger picture on licenses and costs, read Open Source vs Closed Source LLMs. For wider comparisons, see the best AI models hub, or visit the AI Comparison homepage and DeepSeek itself.