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  5. GLM 5.1vsQwen3 Max Thinking
Updated Apr 2026

GLM 5.1vsQwen3 Max Thinking

Qwen3 Max Thinking is cheaper than GLM 5.1 at $1.2/M vs $1.4/M input tokens.

GLM 5.1 and Qwen3 Max Thinking compared across 53 shared prompts
SpecGLM 5.1Qwen3 Max Thinking
Input price$1.4/M tokens$1.2/M tokens
Output price$4.4/M tokens$6/M tokens
Context window203K tokens262K tokens
WeightsOpenClosed
Free API (OpenRouter)NoNo
ReleasedApr 2026Feb 2026
Our Verdict
GLM 5.1
GLM 5.1
Qwen3 Max Thinking
Qwen3 Max Thinking

Not enough votes to call it. On the specs, nothing separates them.

Too close to call

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

GLM 5.1
Input
$1.40
Output
$4.40
1.4× cheaper
Qwen3 Max Thinking
Input
$1.20
1.2× cheaper
Output
$6.00

Qwen3 Max Thinking wins input (1.2× cheaper)·GLM 5.1 wins output (1.4× cheaper)

Where to run it

16 hosts, cheapest first

GLM 5.115 hosts
HostInOutContextUptime
Baidu Qianfanfp8$0.96 in·$3.03 out·203k·100% upSStreamLakefp8$0.97 in·$3.04 out·200k·99.5% upDDeepInfrafp4$1.05 in·$3.50 out·203k·99.9% upSSiliconFlowfp8$1.19 in·$3.74 out·205k·100% upCCrusoefp8$1.20 in·$4.40 out·203k·97.7% upAAtlasCloudfp8$1.26 in·$3.96 out·203k·99.9% up
9 more hostsFewer hosts
Alibaba Cloudfp8$1.33 in·$4.18 out·203k·100% upNNovitafp8$1.38 in·$4.40 out·205k·98.7% upFFriendli$1.40 in·$4.40 out·203k·100% upGGMI Cloudfp8$1.40 in·$4.40 out·203k·99.2% upZ.aifp8$1.40 in·$4.40 out·203k·99.6% upVVenicefp8$1.54 in·$4.84 out·200k·94.2% upCChutesfp8degraded$0.98 in·$3.08 out·203k·90.9% upPPhaladegraded$1.21 in·$4.20 out·203k·90.2% upNNebiusfp8degraded$1.40 in·$4.40 out·203k·91.8% up
Qwen3 Max Thinking1 host
HostInOutContextUptime
Alibaba Cloud$0.78 in·$3.90 out·262k·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 11 Sep 2026.

Writing DNA

Style Comparison

Similarity
35%

Qwen3 Max Thinking uses 225.8x more emoji

GLM 5.1
Qwen3 Max Thinking
54%Vocabulary63%
18wSentence Length14w
0.31Hedging0.23
3.6Bold4.5
2.6Lists2.9
0.00Emoji2.26
0.43Headings0.80
0.11Transitions0.06
Based on 27 + 27 text responses
Research

What we learned reading every model

FAQ

Common questions

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