Models

DeepSeek V3.1 Thinking vs GLM 5.2

Compare DeepSeek V3.1 Thinking from DeepSeek and GLM 5.2 from Z.AI on key metrics including benchmarks, price, context length, and other model features. Access both models and hundreds of others through the AIHubMix API.

DeepSeekDeepSeek V3.1 ThinkingZ.AIGLM 5.2
DeepSeek logo
DeepSeek V3.1 Thinking
DeepSeek · text → text

Thinking mode of DeepSeek-V3.1; DeepSeek V3.1 is a text generation model provided by DeepSeek, featuring a hybrid reasoning architecture that achieves an effective integration of thinking and non-thinking modes.

Input$0.56 /M
Output$1.68 /M
36% off
Z.AI logo
GLM 5.2
Z.AI · text → text

GLM-5.2 is Z.ai’s flagship model for the era of long-horizon tasks. With a truly usable 1M-token context window, it can handle project-level engineering context, execute long-running tasks more reliably, follow engineering standards more consistently, and complete the full development workflow from requirements to multi-platform deployment in a single task.

Input$1.1268$0.7212 /M
Output$3.9438$2.524 /M
Cache read$0.2817$0.1803 /M

Pricing & Specifications

Prices are per million tokens. Time to First Token and throughput are rolling averages measured on AIHubMix.

DeepSeek V3.1 Thinking
GLM 5.2
Input /M
$0.56
$1.1268$0.721236%
Output /M
$1.68
$3.9438$2.52436%
Cache read /M
-
$0.2817$0.180336%
Context length
128,000
1,000,000
Max output
32,000
128,000
Time to First Token
1.3 s
0.7 s
Throughput
31.5 tok/s
35.9 tok/s
Modalities
text
text
Supported Parameters
thinkingtoolsfunction callingstructured outputs
thinkingtoolsfunction callingstructured outputs
API Formats
chat_completions · claude_api
Released
-
June 16, 2026

Promotional prices show the discounted rate; see each model page for promotion windows.

Activity Past 30 Days

Daily traffic served through AIHubMix — how demand for each model is trending.

DeepSeek-V3.1-Thinkglm-5.2

Tokens / day

-

Requests / day

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Performance Past 3 Days

Measured on real AIHubMix traffic, hourly buckets. Gaps mean no traffic in that hour.

DeepSeek-V3.1-Thinkglm-5.2

Throughput (tok/s)

-

TTFT (s)

-

Uptime (%)

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LMArena Benchmarks

LMArena ratings by capability (Bradley-Terry, commonly called Elo). Higher is better.

Text
DeepSeek-V3.1-Thinkglm-5.2
13801420146015001540
Overall
14171472
Coding
14581509
Math
14141476
Hard prompts
14371492
Instruction following
14191465
Multi-turn
14141469
Creative writing
14041451
Longer query
14461482
Chinese
14761517
English
14321480

Source: LMArena (arena.ai) leaderboard, imported by AIHubMix. Models without published ratings are omitted per chart.

Cost calculator

Estimate your monthly bill for the same workload on each model.

DeepSeek V3.1 Thinking
$58.80 /mo
GLM 5.2
$127$81.13 /mo

Monthly = daily × 30. Discounted rates applied where a promotion is active.

FAQ

Which is cheaper: DeepSeek V3.1 Thinking, GLM 5.2?

DeepSeek V3.1 Thinking: $1.68/M output tokens; GLM 5.2: $2.524/M. Use the cost calculator above to estimate your own workload.

How do their coding arena scores compare?

GLM 5.2: 1509; DeepSeek V3.1 Thinking: 1458 (LMArena coding leaderboard).

Which responds faster?

GLM 5.2: 0.7s time to first token measured on AIHubMix; see the live performance charts above for how each model behaves across the day.

How large is each context window?

DeepSeek V3.1 Thinking accepts 128,000 and GLM 5.2 accepts 1,000,000 input tokens. Maximum output per request is 32,000 tokens on DeepSeek V3.1 Thinking and 128,000 tokens on GLM 5.2.

Which one generates tokens faster?

GLM 5.2 at 35.9 tok/s and DeepSeek V3.1 Thinking at 31.5 tok/s, measured as output throughput on AIHubMix — a separate metric from time to first token.

What inputs and capabilities does each model support?

DeepSeek V3.1 Thinking accepts text input and supports thinking, tool calling, function calling and structured outputs; GLM 5.2 accepts text input and supports thinking, tool calling, function calling and structured outputs.

Can I call DeepSeek V3.1 Thinking and GLM 5.2 with the same API key?

Yes. AIHubMix serves every model on this page behind one OpenAI-compatible endpoint, so switching between them is a one-line change to the model field — no second account, key or SDK.

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