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DeepSeek V4.1 Flash vs Nemotron 3.5 Content Safety

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 and Nemotron 3.5 Content Safety are priced within ~10% of each other.

Nemotron 3.5 Content Safety 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
$0.200
Context
1.0M
Released
Sep 10, 2026
Overall score
81.1
reasoningtool callingimage inputprompt caching

nvidia

Nemotron 3.5 Content Safety

Blended / 1M
$0.200
Context
131K
Released
Jun 4, 2026
Overall score
Not evaluated
reasoningimage input

Specs and pricing

MetricDeepSeek V4.1 FlashNemotron 3.5 Content Safety
LiveBench overall

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

81.1
Cost per point

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

$0.0157
Blended price / 1M

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

$0.200$0.200
Input price / 1M$0.100win$0.200
Output price / 1M$0.500$0.200win
Cached input / 1M

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

$0.010
Context window1.0Mwin131K
Max output tokens944Kwin118K

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, Nemotron 3.5 Content Safety below, both out of 100.

Agentic coding
77.3
Coding
80.0
Reasoning
86.7
Mathematics
93.3
Data analysis
79.3
Language
81.2
Instruction following
70.0

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 V4.1 FlashNemotron 3.5 Content Safety
Support chatbot

1.2K in / 400 out × 200K requests

$57.52/mo$64.00/mo
RAG assistant

8K in / 600 out × 100K requests

$74.00/mo$172.00/mo
Coding agent

40K in / 4K out × 20K requests

$69.60/mo$176.00/mo
Document extraction

20K in / 1.5K out × 50K requests

$133.00/mo$215.00/mo
Bulk classification

500 in / 20 out × 5M requests

$255.00/mo$520.00/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 131K.

DeepSeek V4.1 Flash vs Nemotron 3.5 Content Safety FAQ

Which is better, DeepSeek V4.1 Flash or Nemotron 3.5 Content Safety?

DeepSeek V4.1 Flash and Nemotron 3.5 Content Safety are priced within ~10% of each other. Nemotron 3.5 Content Safety 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 Nemotron 3.5 Content Safety?

They cost about the same. Both land near $0.200 per million tokens on a 3:1 input:output blend, so price is unlikely to be the deciding factor between them.

Does DeepSeek V4.1 Flash or Nemotron 3.5 Content Safety have a bigger context window?

DeepSeek V4.1 Flash has the larger context window: 1.0M for DeepSeek V4.1 Flash against 131K for Nemotron 3.5 Content Safety. 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 Nemotron 3.5 Content Safety support prompt caching?

DeepSeek V4.1 Flash publishes a cached-input rate of $0.010 per million tokens against a full input rate of $0.100. The catalogue lists no separate cached rate for Nemotron 3.5 Content Safety, 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.
  • ScoresLiveBench 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.