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DeepSeek V4 Flash 0731 vs DeepSeek V4 Flash Vision Exp

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.

OpenRouter + LiveBenchAll comparisonsFull leaderboard

DeepSeek V4 Flash Vision Exp is the better model, at roughly the same price.

DeepSeek V4 Flash Vision Exp leads by 2.6 points overall and the two list within about 10% of each other, so the cheaper-but-weaker trade-off does not apply. Price parity plus a score gap usually makes this an easy call. DeepSeek V4 Flash Vision Exp also leads on measured cost per point of capability, at $0.0277 per point.

deepseek

DeepSeek V4 Flash 0731

Blended / 1M
$0.324
Context
1.0M
Released
Jul 31, 2026
Overall score
74.2
reasoningtool callingprompt caching

deepseek

DeepSeek V4 Flash Vision Exp

Blended / 1M
$0.323
Context
1.0M
Released
Aug 21, 2026
Overall score
76.8
reasoningtool callingimage inputprompt caching

Specs and pricing

MetricDeepSeek V4 Flash 0731DeepSeek V4 Flash Vision Exp
LiveBench overall

Mean of the seven LiveBench category scores, 0–100. Higher is better.

74.276.8win
Cost per point

Measured benchmark spend divided by overall score — dollars per point of capability.

$0.0356$0.0277win
Blended price / 1M

3:1 input:output mix, the usual shape of production traffic.

$0.324$0.323
Input price / 1M$0.0051win$0.216
Output price / 1M$1.28$0.647win
Cached input / 1M

Price of an input token served from the prompt cache, where the provider publishes one.

$0.0051win$0.0069
Context window1.0M1.0M
Max output tokens944Kwin262K

Benchmarks by category

An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — DeepSeek V4 Flash 0731 on top, DeepSeek V4 Flash Vision Exp below, both out of 100.

Agentic coding
46.8
65.1
Coding
75.0
68.2
Reasoning
86.6
85.4
Mathematics
86.8
87.8
Data analysistoo close to call
79.3
79.5
Language
79.2
80.4
Instruction following
65.5
71.0

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.

WorkloadDeepSeek V4 Flash 0731DeepSeek V4 Flash Vision Exp
Support chatbot

1.2K in / 400 out × 200K requests

$103.62/mo$88.46/mo
RAG assistant

8K in / 600 out × 100K requests

$80.88/mo$127.79/mo
Coding agent

40K in / 4K out × 20K requests

$106.48/mo$107.33/mo
Document extraction

20K in / 1.5K out × 50K requests

$101.10/mo$253.67/mo
Bulk classification

500 in / 20 out × 5M requests

$140.75/mo$499.31/mo
Run these two through the cost calculator

Which should you pick?

You are running this at volume

DeepSeek V4 Flash Vision Exp

Lowest measured cost per point of capability at $0.0277 per point — the gap compounds with every request.

Quality matters more than the bill

DeepSeek V4 Flash Vision Exp

Highest overall LiveBench score of the two at 76.8.

The workload is coding or agentic work

DeepSeek V4 Flash Vision Exp

Leads on agentic coding — 65.1 against 46.8.

DeepSeek V4 Flash 0731 vs DeepSeek V4 Flash Vision Exp FAQ

Which is better, DeepSeek V4 Flash 0731 or DeepSeek V4 Flash Vision Exp?

DeepSeek V4 Flash Vision Exp is the better model, at roughly the same price. DeepSeek V4 Flash Vision Exp leads by 2.6 points overall and the two list within about 10% of each other, so the cheaper-but-weaker trade-off does not apply. Price parity plus a score gap usually makes this an easy call. DeepSeek V4 Flash Vision Exp also leads on measured cost per point of capability, at $0.0277 per point.

Is DeepSeek V4 Flash 0731 cheaper than DeepSeek V4 Flash Vision Exp?

They cost about the same. Both land near $0.324 per million tokens on a 3:1 input:output blend, so price is unlikely to be the deciding factor between them.

DeepSeek V4 Flash 0731 vs DeepSeek V4 Flash Vision Exp: which scores higher on benchmarks?

DeepSeek V4 Flash 0731 scores 74.2 and DeepSeek V4 Flash Vision Exp scores 76.8 overall on LiveBench, the mean of its seven categories. That is a 2.6-point lead for DeepSeek V4 Flash Vision Exp. Category scores differ from the overall figure — a model can lead on reasoning and trail on coding, which the per-category table above breaks out.

Which gives better value for money, DeepSeek V4 Flash 0731 or DeepSeek V4 Flash Vision Exp?

DeepSeek V4 Flash Vision Exp. Cost per point divides the measured dollars LiveBench spent running the benchmark by the score it earned, so it captures something token pricing misses: a reasoning model can emit many times more tokens than its per-token rate suggests. DeepSeek V4 Flash 0731 works out at $0.0356 per point and DeepSeek V4 Flash Vision Exp at $0.0277.

Does DeepSeek V4 Flash 0731 or DeepSeek V4 Flash Vision Exp have a bigger context window?

They are effectively the same — 1.0M for DeepSeek V4 Flash 0731 and 1.0M for DeepSeek V4 Flash Vision Exp.

Do DeepSeek V4 Flash 0731 and DeepSeek V4 Flash Vision Exp support prompt caching?

Both publish a cached-input rate: $0.0051 per million for DeepSeek V4 Flash 0731 and $0.0069 for DeepSeek V4 Flash Vision Exp, against full input rates of $0.0051 and $0.216. 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 2026-06-25, 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.