// head_to_head
DeepSeek V4 Flash Vision Exp vs Gemma 4 31B
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.
Gemma 4 31B is the cheaper of the two; neither can be ranked on quality here.
Gemma 4 31B 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 Flash Vision Exp
- Blended / 1M
- $0.330
- Context
- 1.0M
- Released
- Aug 21, 2026
- Overall score
- 76.8
Gemma 4 31B
- Blended / 1M
- $0.152
- Context
- 262K
- Released
- Apr 2, 2026
- Overall score
- Not evaluated
Specs and pricing
| Metric | DeepSeek V4 Flash Vision Exp | Gemma 4 31B |
|---|---|---|
| LiveBench overall Mean of the seven LiveBench category scores, 0–100. Higher is better. | 76.8 | — |
| Cost per point Measured benchmark spend divided by overall score — dollars per point of capability. | $0.0277 | — |
| Blended price / 1M 3:1 input:output mix, the usual shape of production traffic. | $0.330 | $0.152win |
| Input price / 1M | $0.220 | $0.090win |
| Output price / 1M | $0.660 | $0.340win |
| Cached input / 1M Price of an input token served from the prompt cache, where the provider publishes one. | $0.0070win | $0.050 |
| Context window | 1.0Mwin | 262K |
| Max output tokens | 944Kwin | 16K |
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 Vision Exp on top, Gemma 4 31B 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 Flash Vision Exp | Gemma 4 31B |
|---|---|---|
| Support chatbot 1.2K in / 400 out × 200K requests | $90.26/mo | $45.92/mo |
| RAG assistant 8K in / 600 out × 100K requests | $130.40/mo | $76.40/mo |
| Coding agent 40K in / 4K out × 20K requests | $109.52/mo | $76.80/mo |
| Document extraction 20K in / 1.5K out × 50K requests | $258.85/mo | $113.50/mo |
| Bulk classification 500 in / 20 out × 5M requests | $509.50/mo | $239.00/mo |
Which should you pick?
You need to fit large documents in one call
DeepSeek V4 Flash Vision Exp
Wider context window — 1.0M against 262K.
You are cost-constrained
Gemma 4 31B
Cheaper on blended list price at $0.152 per million tokens.
DeepSeek V4 Flash Vision Exp vs Gemma 4 31B FAQ
Which is better, DeepSeek V4 Flash Vision Exp or Gemma 4 31B?
Gemma 4 31B is the cheaper of the two; neither can be ranked on quality here. Gemma 4 31B 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 Flash Vision Exp cheaper than Gemma 4 31B?
Gemma 4 31B is cheaper. On a 3:1 input:output blend, DeepSeek V4 Flash Vision Exp lists at $0.330 per million tokens and Gemma 4 31B at $0.152 — Gemma 4 31B is 2.2× cheaper. Input and output are priced separately — DeepSeek V4 Flash Vision Exp charges $0.220 in and $0.660 out, Gemma 4 31B charges $0.090 and $0.340 — so the model that looks cheaper flips depending on how output-heavy your workload is.
Does DeepSeek V4 Flash Vision Exp or Gemma 4 31B have a bigger context window?
DeepSeek V4 Flash Vision Exp has the larger context window: 1.0M for DeepSeek V4 Flash Vision Exp against 262K for Gemma 4 31B. Note that a window you can fill is not a window you should fill — retrieval quality usually degrades well before the limit, and you pay for every token you put in it.
Do DeepSeek V4 Flash Vision Exp and Gemma 4 31B support prompt caching?
Both publish a cached-input rate: $0.0070 per million for DeepSeek V4 Flash Vision Exp and $0.050 for Gemma 4 31B, against full input rates of $0.220 and $0.090. 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.