// head_to_head
DeepSeek V4.1 Flash 1017 vs DeepSeek V4 Pro 0423
Published LiveBench scores across all seven categories, live list pricing, context windows, and the measured cost of a point of capability — for both models, side by side.
DeepSeek V4.1 Flash 1017 is the cheaper of the two; neither can be ranked on quality here.
DeepSeek V4 Pro 0423 does not have a published LiveBench run, so this comparison covers price, context and declared capabilities only. A missing score means "not evaluated", not "worse" — the right way to separate these two is an eval on your own workload.
deepseek
DeepSeek V4.1 Flash 1017
- Blended / 1M
- $0.262
- Context
- 1.0M
- Released
- Oct 17, 2026
- Overall score
- 74.0
deepseek
DeepSeek V4 Pro 0423
- Blended / 1M
- $1.19
- Context
- 1.0M
- Released
- Apr 24, 2026
- Overall score
- Not evaluated
Specs and pricing
| Metric | DeepSeek V4.1 Flash 1017 | DeepSeek V4 Pro 0423 |
|---|---|---|
| LiveBench overall Weighted mean of the seven LiveBench category scores, 0–100. Higher is better. | 74.0 | — |
| Cost per point Measured benchmark spend divided by overall score — dollars per point of capability. | $0.0018 | — |
| Blended price / 1M 3:1 input:output mix, the usual shape of production traffic. | $0.262win | $1.19 |
| Input price / 1M | $0.150win | $0.955 |
| Output price / 1M | $0.600win | $1.91 |
| Cached input / 1M Price of an input token served from the prompt cache, where the provider publishes one. | $0.0030win | $0.080 |
| Context window | 1.0M | 1.0M |
| Max output tokens | 393K | 384K |
Benchmarks by category
An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — DeepSeek V4.1 Flash 1017 on top, DeepSeek V4 Pro 0423 below, both out of 100.
What each one costs to run
Per-token prices are hard to feel. These are monthly list costs for both models across five workload shapes, using each provider's published cached-input rate where there is one.
| Workload | DeepSeek V4.1 Flash 1017 | DeepSeek V4 Pro 0423 |
|---|---|---|
| Support chatbot 1.2K in / 400 out × 200K requests | $73.42/mo | $319.06/mo |
| RAG assistant 8K in / 600 out × 100K requests | $97.20/mo | $528.58/mo |
| Coding agent 40K in / 4K out × 20K requests | $85.68/mo | $426.68/mo |
| Document extraction 20K in / 1.5K out × 50K requests | $187.65/mo | $1,055/mo |
| Bulk classification 500 in / 20 out × 5M requests | $361.50/mo | $2,141/mo |
Which should you pick?
You are cost-constrained
DeepSeek V4.1 Flash 1017
Cheaper on blended list price at $0.262 per million tokens.
DeepSeek V4.1 Flash 1017 vs DeepSeek V4 Pro 0423 FAQ
Which is better, DeepSeek V4.1 Flash 1017 or DeepSeek V4 Pro 0423?
DeepSeek V4.1 Flash 1017 is the cheaper of the two; neither can be ranked on quality here. DeepSeek V4 Pro 0423 does not have a published LiveBench run, so this comparison covers price, context and declared capabilities only. A missing score means "not evaluated", not "worse" — the right way to separate these two is an eval on your own workload.
Is DeepSeek V4.1 Flash 1017 cheaper than DeepSeek V4 Pro 0423?
DeepSeek V4.1 Flash 1017 is cheaper. On a 3:1 input:output blend, DeepSeek V4.1 Flash 1017 lists at $0.262 per million tokens and DeepSeek V4 Pro 0423 at $1.19 — DeepSeek V4.1 Flash 1017 is 4.5× cheaper. Input and output are priced separately — DeepSeek V4.1 Flash 1017 charges $0.150 in and $0.600 out, DeepSeek V4 Pro 0423 charges $0.955 and $1.91 — so the model that looks cheaper flips depending on how output-heavy your workload is.
Does DeepSeek V4.1 Flash 1017 or DeepSeek V4 Pro 0423 have a bigger context window?
They are effectively the same — 1.0M for DeepSeek V4.1 Flash 1017 and 1.0M for DeepSeek V4 Pro 0423.
Do DeepSeek V4.1 Flash 1017 and DeepSeek V4 Pro 0423 support prompt caching?
Both publish a cached-input rate: $0.0030 per million for DeepSeek V4.1 Flash 1017 and $0.080 for DeepSeek V4 Pro 0423, against full input rates of $0.150 and $0.955. On a workload with a long stable prefix — a system prompt, a tool schema, a retrieved corpus — that changes the economics more than the headline price does.
Related comparisons
How these numbers are produced
- Price — provider list price from OpenRouter, refreshed every 15 minutes. “Blended” is a 3:1 input:output mix.
- Scores — LiveBench release 2026-10-25, using their own category map. Each model shows its strongest published run. A blank means “not evaluated”, never “bad”.
- Cost per point — the measured dollars LiveBench spent on the run, divided by the score it earned.
- “Win” — awarded only past a threshold: one full point on a benchmark score, 10% on a price, 25% on a context window. Anything tighter reports as a tie, because effort settings alone move a LiveBench score by more than that.
Published benchmarks rank models on someone else's tasks. Before committing, see LLM & agent evaluation for building an eval on your own.