pvakati-tech.ai

// head_to_head

DeepSeek V4.1 Flash vs Gemini 4 Argon

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

Gemini 4 Argon scores higher, DeepSeek V4.1 Flash costs less — it depends on your workload.

Gemini 4 Argon is ahead by 6.8 points overall, and DeepSeek V4.1 Flash lists 21× cheaper per blended million tokens. Whether 6.8 points is worth that depends on how much a wrong answer costs you. DeepSeek V4.1 Flash also leads on measured cost per point of capability, at $0.0895 per point.

deepseek

DeepSeek V4.1 Flash

Blended / 1M
$0.191
Context
1.0M
Released
Sep 10, 2026
Overall score
77.3
reasoningtool callingimage inputprompt caching

google

Gemini 4 Argon

Blended / 1M
$4.00
Context
1.0M
Released
Oct 13, 2026
Overall score
84.1
reasoningtool callingaudio inputfile inputimage inputvideo inputprompt caching

Specs and pricing

MetricDeepSeek V4.1 FlashGemini 4 Argon
LiveBench overall

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

77.384.1win
Cost per point

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

$0.0895win$1.24
Blended price / 1M

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

$0.191win$4.00
Input price / 1M$0.044win$2.00
Output price / 1M$0.630win$10.00
Cached input / 1M

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

$0.0054win$0.100
Context window1.0M1.0M
Max output tokens944Kwin66K

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, Gemini 4 Argon below, both out of 100.

Coding
85.4
89.7
Reasoning
86.7
95.1
Data analysis
79.3
85.2

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 FlashGemini 4 Argon
Support chatbot

1.2K in / 400 out × 200K requests

$58.20/mo$1,143/mo
RAG assistant

8K in / 600 out × 100K requests

$57.60/mo$1,440/mo
Coding agent

40K in / 4K out × 20K requests

$64.01/mo$1,336/mo
Document extraction

20K in / 1.5K out × 50K requests

$89.42/mo$2,655/mo
Bulk classification

500 in / 20 out × 5M requests

$153.90/mo$5,050/mo
Run these two through the cost calculator

Which should you pick?

You are running this at volume

DeepSeek V4.1 Flash

Lowest measured cost per point of capability at $0.0895 per point — the gap compounds with every request.

Quality matters more than the bill

Gemini 4 Argon

Highest overall LiveBench score of the two at 84.1.

The workload is coding or agentic work

Gemini 4 Argon

Leads on coding — 89.7 against 85.4.

DeepSeek V4.1 Flash vs Gemini 4 Argon FAQ

Which is better, DeepSeek V4.1 Flash or Gemini 4 Argon?

Gemini 4 Argon scores higher, DeepSeek V4.1 Flash costs less — it depends on your workload. Gemini 4 Argon is ahead by 6.8 points overall, and DeepSeek V4.1 Flash lists 21× cheaper per blended million tokens. Whether 6.8 points is worth that depends on how much a wrong answer costs you. DeepSeek V4.1 Flash also leads on measured cost per point of capability, at $0.0895 per point.

Is DeepSeek V4.1 Flash cheaper than Gemini 4 Argon?

DeepSeek V4.1 Flash is cheaper. On a 3:1 input:output blend, DeepSeek V4.1 Flash lists at $0.191 per million tokens and Gemini 4 Argon at $4.00 — DeepSeek V4.1 Flash is 21× cheaper. Input and output are priced separately — DeepSeek V4.1 Flash charges $0.044 in and $0.630 out, Gemini 4 Argon charges $2.00 and $10.00 — so the model that looks cheaper flips depending on how output-heavy your workload is.

DeepSeek V4.1 Flash vs Gemini 4 Argon: which scores higher on benchmarks?

DeepSeek V4.1 Flash scores 77.3 and Gemini 4 Argon scores 84.1 overall on LiveBench, the mean of its seven categories. That is a 6.8-point lead for Gemini 4 Argon. 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 V4.1 Flash or Gemini 4 Argon?

DeepSeek V4.1 Flash. 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 V4.1 Flash works out at $0.0895 per point and Gemini 4 Argon at $1.24.

Does DeepSeek V4.1 Flash or Gemini 4 Argon have a bigger context window?

They are effectively the same — 1.0M for DeepSeek V4.1 Flash and 1.0M for Gemini 4 Argon.

Do DeepSeek V4.1 Flash and Gemini 4 Argon support prompt caching?

Both publish a cached-input rate: $0.0054 per million for DeepSeek V4.1 Flash and $0.100 for Gemini 4 Argon, against full input rates of $0.044 and $2.00. 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 2026-09-02, 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.