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  5. Claude Opus 4.6vsQwen3.5 397B A17B
Updated Feb 2026

Claude Opus 4.6vsQwen3.5 397B A17B

Qwen3.5 397B A17B is cheaper than Claude Opus 4.6 at $0.6/M vs $5/M input tokens.

Claude Opus 4.6 and Qwen3.5 397B A17B compared across 53 shared prompts
SpecClaude Opus 4.6Qwen3.5 397B A17B
Input price$5/M tokens$0.6/M tokens
Output price$25/M tokens$3.6/M tokens
Context window1.0M tokens262K tokens
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedFeb 2026Feb 2026
SWE-bench Verified80.8%76.4%
Our Verdict
Claude Opus 4.6
Claude Opus 4.6
Qwen3.5 397B A17B
Qwen3.5 397B A17BRunner-up

Not enough votes to call it. On the specs, Claude Opus 4.6 has the edge: bigger context window, major provider backing.

Qwen3.5 397B A17B costs 6.9x less per token.

Too close to call

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

Claude Opus 4.6
Input
$5.00
Output
$25.00
Qwen3.5 397B A17B
Input
$0.60
8.3× cheaper
Output
$3.60
6.9× cheaper

Qwen3.5 397B A17B is cheaper on both: 8.3× input, 6.9× output.

Where to run it

14 hosts, cheapest first

Claude Opus 4.64 hosts
HostInOutContextUptime
Amazon Bedrock$5.00 in·$25.00 out·1M·99.8% upAzure AI Foundry$5.00 in·$25.00 out·1M·100% upAnthropic$5.00 in·$25.00 out·1M·99.9% upGoogle Vertex AI$5.00 in·$25.00 out·1M·99.8% up
Qwen3.5 397B A17B10 hosts
HostInOutContextUptime
Alibaba Cloud$0.39 in·$2.34 out·262k·99.9% upDDeepInfrafp8$0.45 in·$3.00 out·262k·98.5% upPParasailfp8$0.50 in·$3.60 out·262k·99.8% upAAtlasCloudfp8$0.55 in·$3.50 out·262k·97.3% upDDigitalOcean$0.55 in·$3.50 out·131k·98.7% upPPhala$0.55 in·$3.50 out·262k·98.9% up
4 more hostsFewer hosts
GGMI Cloudfp8$0.60 in·$3.60 out·262k·92.2% upNNovita$0.60 in·$3.60 out·262k·98.6% upSStreamLake$0.60 in·$3.60 out·256k·93.2% upVVenice$0.75 in·$4.50 out·128k·96.2% up

Per million tokens. Prices and uptime via OpenRouter, checked 12 Sep 2026.

Writing DNA

Style Comparison

Similarity
43%

Qwen3.5 397B A17B uses 7.0x more transitions

Claude Opus 4.6
Qwen3.5 397B A17B
56%Vocabulary54%
33wSentence Length14w
0.73Hedging0.39
5.3Bold6.9
2.7Lists4.2
1.16Emoji0.23
1.23Headings0.93
0.02Transitions0.17
Based on 26 + 23 text responses
Research

What we learned reading every model

FAQ

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