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Claude Sonnet 5.5 vs DeepSeek V4.1 Flash 1017

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 1017 is the cheaper of the two; neither can be ranked on quality here.

DeepSeek V4.1 Flash 1017 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.

anthropic

Claude Sonnet 5.5

Blended / 1M
$4.00
Context
1M
Released
Sep 28, 2026
Overall score
82.5
reasoningtool callingimage inputfile inputprompt caching

deepseek

DeepSeek V4.1 Flash 1017

Blended / 1M
$0.262
Context
1.0M
Released
Oct 17, 2026
Overall score
Not evaluated
reasoningtool callingimage inputprompt caching

Specs and pricing

MetricClaude Sonnet 5.5DeepSeek V4.1 Flash 1017
LiveBench overall

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

82.5—
Cost per point

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

$2.58—
Blended price / 1M

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

$4.00$0.262win
Input price / 1M$2.00$0.150win
Output price / 1M$10.00$0.600win
Cached input / 1M

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

$0.100$0.0030win
Context window1M1.0M
Max output tokens128K393Kwin

Benchmarks by category

An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — Claude Sonnet 5.5 on top, DeepSeek V4.1 Flash 1017 below, both out of 100.

Coding
94.7
—
Reasoning
91.6
—
Data analysis
59.5
—

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.

WorkloadClaude Sonnet 5.5DeepSeek V4.1 Flash 1017
Support chatbot

1.2K in / 400 out × 200K requests

$1,143/mo$73.42/mo
RAG assistant

8K in / 600 out × 100K requests

$1,440/mo$97.20/mo
Coding agent

40K in / 4K out × 20K requests

$1,336/mo$85.68/mo
Document extraction

20K in / 1.5K out × 50K requests

$2,655/mo$187.65/mo
Bulk classification

500 in / 20 out × 5M requests

$5,050/mo$361.50/mo
Run these two through the cost calculator

Which should you pick?

You are cost-constrained

DeepSeek V4.1 Flash 1017

Cheaper on blended list price at $0.262 per million tokens.

Claude Sonnet 5.5 vs DeepSeek V4.1 Flash 1017 FAQ

Which is better, Claude Sonnet 5.5 or DeepSeek V4.1 Flash 1017?

DeepSeek V4.1 Flash 1017 is the cheaper of the two; neither can be ranked on quality here. DeepSeek V4.1 Flash 1017 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 Claude Sonnet 5.5 cheaper than DeepSeek V4.1 Flash 1017?

DeepSeek V4.1 Flash 1017 is cheaper. On a 3:1 input:output blend, Claude Sonnet 5.5 lists at $4.00 per million tokens and DeepSeek V4.1 Flash 1017 at $0.262 — DeepSeek V4.1 Flash 1017 is 15× cheaper. Input and output are priced separately — Claude Sonnet 5.5 charges $2.00 in and $10.00 out, DeepSeek V4.1 Flash 1017 charges $0.150 and $0.600 — so the model that looks cheaper flips depending on how output-heavy your workload is.

Does Claude Sonnet 5.5 or DeepSeek V4.1 Flash 1017 have a bigger context window?

They are effectively the same — 1M for Claude Sonnet 5.5 and 1.0M for DeepSeek V4.1 Flash 1017.

Do Claude Sonnet 5.5 and DeepSeek V4.1 Flash 1017 support prompt caching?

Both publish a cached-input rate: $0.100 per million for Claude Sonnet 5.5 and $0.0030 for DeepSeek V4.1 Flash 1017, against full input rates of $2.00 and $0.150. 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.