vakati-tech.ai

// head_to_head

DeepSeek V4.1 Flash 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.

OpenRouter + LiveBenchAll comparisonsFull leaderboard

DeepSeek V4.1 Flash is the cheaper of the two; neither can be ranked on quality here.

DeepSeek V4.1 Flash 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

Blended / 1M
$0.180
Context
1.0M
Released
Sep 10, 2026
Overall score
Not evaluated
reasoningtool callingimage inputprompt caching

google

Gemma 4 31B

Blended / 1M
$0.250
Context
262K
Released
Apr 2, 2026
Overall score
38.7
reasoningtool callingimage inputvideo input

Specs and pricing

MetricDeepSeek V4.1 FlashGemma 4 31B
LiveBench overall

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

—38.7
Cost per point

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

—$0.0017
Blended price / 1M

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

$0.180win$0.250
Input price / 1M$0.051win$0.200
Output price / 1M$0.567$0.400win
Cached input / 1M

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

$0.018—
Context window1.0Mwin262K
Max output tokens944Kwin16K

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 on top, Gemma 4 31B below, both out of 100.

Long-horizon agentic
—
10.7
Coding
—
49.0
Reasoning
—
68.3
Browser
—
0.0
Data analysis
—
53.3
Research
—
44.4
Documents & design
—
58.4

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 V4.1 FlashGemma 4 31B
Support chatbot

1.2K in / 400 out × 200K requests

$55.22/mo$80.00/mo
RAG assistant

8K in / 600 out × 100K requests

$61.62/mo$184.00/mo
Coding agent

40K in / 4K out × 20K requests

$67.68/mo$192.00/mo
Document extraction

20K in / 1.5K out × 50K requests

$91.88/mo$230.00/mo
Bulk classification

500 in / 20 out × 5M requests

$167.70/mo$540.00/mo
Run these two through the cost calculator

Which should you pick?

You need to fit large documents in one call

DeepSeek V4.1 Flash

Wider context window — 1.0M against 262K.

DeepSeek V4.1 Flash vs Gemma 4 31B FAQ

Which is better, DeepSeek V4.1 Flash or Gemma 4 31B?

DeepSeek V4.1 Flash is the cheaper of the two; neither can be ranked on quality here. DeepSeek V4.1 Flash 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 cheaper than Gemma 4 31B?

DeepSeek V4.1 Flash is cheaper. On a 3:1 input:output blend, DeepSeek V4.1 Flash lists at $0.180 per million tokens and Gemma 4 31B at $0.250 — DeepSeek V4.1 Flash is 39% cheaper. Input and output are priced separately — DeepSeek V4.1 Flash charges $0.051 in and $0.567 out, Gemma 4 31B charges $0.200 and $0.400 — so the model that looks cheaper flips depending on how output-heavy your workload is.

Does DeepSeek V4.1 Flash or Gemma 4 31B have a bigger context window?

DeepSeek V4.1 Flash has the larger context window: 1.0M for DeepSeek V4.1 Flash 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 V4.1 Flash and Gemma 4 31B support prompt caching?

DeepSeek V4.1 Flash publishes a cached-input rate of $0.018 per million tokens against a full input rate of $0.051. The catalogue lists no separate cached rate for Gemma 4 31B, which means the provider does not price it separately here — not that caching is unavailable.

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.