LiteLLMModels

DeepSeek V4 Flash vs DeepSeek V4 Pro

As of October 21, 2026, DeepSeek V4 Pro costs 340% more per input token than DeepSeek V4 Flash ($1.32 vs $0.30 per 1M), and both have a 1M-token context window.

Prices from LiteLLM's price fileChecked

DeepSeek V4 Flash vs DeepSeek V4 Pro side by side

Headline prices in US dollars per 1M tokens: each model's own lab where it sells it, otherwise its cheapest provider. Source: LiteLLM model price file, as of October 21, 2026.
DeepSeek V4 FlashDeepSeek V4 Pro
Input, per 1M tokens$0.30$1.32
Output, per 1M tokens$1.20$3.96
Cache read, per 1M tokens$0.006$0.044
Cache write, per 1M tokens$0$0
Context window1,000,000 tokens1,000,000 tokens
Max output393,216 tokens393,216 tokens
Image inputYesNo
Tool callingYesYes
Structured output (JSON)YesYes
Prompt cachingYesYes
ReasoningYesYes
Providers on LiteLLM2318
Price shown is fromDeepSeekDeepSeek
Added to LiteLLMJune 2026June 2026

Cheapest provider for each

Benchmark scores

From the Epoch AI Benchmarking Hub (CC BY 4.0), data as of August 27, 2026. Some results were run by Epoch and others collected by Epoch from each benchmark's own leaderboard, linked in the first column. Each model's best reported reasoning setting is shown in brackets. Higher is better. Only benchmarks with a score for both models are shown.
BenchmarkDeepSeek V4 FlashDeepSeek V4 Pro
Coding and agents
FrontierCode18.8%17.6% (none)
Reasoning and knowledge
GPQA Diamond91.0% (max)90.9% (high)
ARC-AGI-261.4% (max)61.3% (max)
SimpleQA Verified33.6% (max)47.0% (max)
Math
FrontierMath (tiers 1-3)57.5% (max)45.3% (max)
FrontierMath (tier 4)24.4% (max)2.4% (max)
OTIS Mock AIME 2024-202594.4% (max)96.7% (max)

When to pick which

Pick DeepSeek V4 Flash for

  • Costs 77% less per input token: $0.30 vs $1.32 per 1M.
  • Supports image input, which DeepSeek V4 Pro doesn't list.

From differences in the data above only; where the data is equal, no reason is given.

Call DeepSeek V4 Flash or DeepSeek V4 Pro with LiteLLM

Both use the OpenAI format through LiteLLM, so switching is a model name change. Set each provider's API key in the environment first.

Python SDK
from litellm import completion

messages = [{"role": "user", "content": "Hello!"}]

# DeepSeek V4 Flash
response = completion(model="deepseek-v4-flash", messages=messages)

# DeepSeek V4 Pro
response = completion(model="deepseek-v4-pro", messages=messages)

# DeepSeek V4 Flash, falling back to DeepSeek V4 Pro if the call fails
response = completion(model="deepseek-v4-flash", messages=messages, fallbacks=["deepseek-v4-pro"])

FAQ

Which is cheaper, DeepSeek V4 Flash or DeepSeek V4 Pro?

DeepSeek V4 Flash is cheaper at 3 input tokens per output token: $0.525 per 1M tokens blended ($0.30 input, $1.20 output), versus $1.98 ($1.32 and $3.96) for DeepSeek V4 Pro, as of October 21, 2026.

Which has the larger context window, DeepSeek V4 Flash or DeepSeek V4 Pro?

Both have a 1,000,000-token context window.

Can I switch from DeepSeek V4 Flash to DeepSeek V4 Pro without changing my code?

Yes. Through LiteLLM both use the OpenAI format, so switching means changing the model name from "deepseek-v4-flash" to "deepseek-v4-pro", or pointing a LiteLLM gateway model alias at the other model. You can also use one as a fallback for the other.