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Gemini 4 Argon vs Mistral Large 4

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, Mistral Large 4 costs less — it depends on your workload.

Gemini 4 Argon is ahead by 35.4 points overall, and Mistral Large 4 lists 1.9× cheaper per blended million tokens. Whether 35.4 points is worth that depends on how much a wrong answer costs you. Mistral Large 4 also leads on measured cost per point of capability, at $0.0162 per point.

google

Gemini 4 Argon

Blended / 1M
$4.00
Context
1.0M
Released
Oct 13, 2026
Overall score
79.3
reasoningtool callingaudio inputfile inputimage inputvideo inputprompt caching

mistralai

Mistral Large 4

Blended / 1M
$2.06
Context
1.0M
Released
Oct 6, 2026
Overall score
43.9
reasoningtool callingimage inputprompt caching

Specs and pricing

MetricGemini 4 ArgonMistral Large 4
LiveBench overall

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

79.3win43.9
Cost per point

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

$0.0207$0.0162win
Blended price / 1M

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

$4.00$2.06win
Input price / 1M$2.00$1.36win
Output price / 1M$10.00$4.18win
Cached input / 1M

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

$0.100win$0.140
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 — Gemini 4 Argon on top, Mistral Large 4 below, both out of 100.

Long-horizon agentic
61.2
8.8
Coding
89.7
60.0
Reasoning
95.1
83.9
Browser
82.8
0.6
Data analysis
85.2
76.5
Research
83.1
28.1
Documents & design
73.7
65.6

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.

WorkloadGemini 4 ArgonMistral Large 4
Support chatbot

1.2K in / 400 out × 200K requests

$1,143/mo$572.96/mo
RAG assistant

8K in / 600 out × 100K requests

$1,440/mo$850.80/mo
Coding agent

40K in / 4K out × 20K requests

$1,336/mo$739.20/mo
Document extraction

20K in / 1.5K out × 50K requests

$2,655/mo$1,612/mo
Bulk classification

500 in / 20 out × 5M requests

$5,050/mo$3,208/mo
Run these two through the cost calculator

Which should you pick?

You are running this at volume

Mistral Large 4

Lowest measured cost per point of capability at $0.0162 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 79.3.

The workload is coding or agentic work

Gemini 4 Argon

Leads on long-horizon agentic — 61.2 against 8.8.

Gemini 4 Argon vs Mistral Large 4 FAQ

Which is better, Gemini 4 Argon or Mistral Large 4?

Gemini 4 Argon scores higher, Mistral Large 4 costs less — it depends on your workload. Gemini 4 Argon is ahead by 35.4 points overall, and Mistral Large 4 lists 1.9× cheaper per blended million tokens. Whether 35.4 points is worth that depends on how much a wrong answer costs you. Mistral Large 4 also leads on measured cost per point of capability, at $0.0162 per point.

Is Gemini 4 Argon cheaper than Mistral Large 4?

Mistral Large 4 is cheaper. On a 3:1 input:output blend, Gemini 4 Argon lists at $4.00 per million tokens and Mistral Large 4 at $2.06 — Mistral Large 4 is 1.9× cheaper. Input and output are priced separately — Gemini 4 Argon charges $2.00 in and $10.00 out, Mistral Large 4 charges $1.36 and $4.18 — so the model that looks cheaper flips depending on how output-heavy your workload is.

Gemini 4 Argon vs Mistral Large 4: which scores higher on benchmarks?

Gemini 4 Argon scores 79.3 and Mistral Large 4 scores 43.9 overall on LiveBench, the weighted mean of its seven categories. That is a 35.4-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, Gemini 4 Argon or Mistral Large 4?

Mistral Large 4. 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. Gemini 4 Argon works out at $0.0207 per point and Mistral Large 4 at $0.0162.

Does Gemini 4 Argon or Mistral Large 4 have a bigger context window?

They are effectively the same — 1.0M for Gemini 4 Argon and 1.0M for Mistral Large 4.

Do Gemini 4 Argon and Mistral Large 4 support prompt caching?

Both publish a cached-input rate: $0.100 per million for Gemini 4 Argon and $0.140 for Mistral Large 4, against full input rates of $2.00 and $1.36. 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.