Skip to main content
AI Choice Engine

Model comparison

GLM 5.2 vs Qwen3-235B-A22B

Z.ai against Qwen, compared on context, price, and verified benchmark results.

Catalog record checked September 26, 2026Individual provider fields may changeEvidence confidence: High — see receipts below

Z.ai

GLM 5.2

Balanced · Open weights

vs

Qwen

Qwen3-235B-A22B

Balanced · Open weights

AI model capability comparison
SpecificationGLM 5.2Qwen3-235B-A22B
ProviderZ.aiQwen
TierBalancedBalanced
Context windowWinner: 1M128K
Max outputWinner: 128K33K
Input / 1M tokens$1.40Winner: $0.70
Output / 1M tokens$4.40Winner: $2.80
WeightsOpenOpen
Parametersopen MoE235B total / 22B active (MoE)
Reasoning levelslow, high, maxlow, high, max
Modalitiestexttext
LicenseNot disclosedUnverifiedApache 2.0
API model idglm-5.2qwen3-235b-a22b
ReleasedJune 16, 2026April 29, 2025
Artificial Analysis Intelligence Index [max] (2026-09-26)33.7Not verifiedUnverified
Artificial Analysis Intelligence Index (2026-09-26)Not verifiedUnverified9.5

Prices are USD per million tokens at standard rates, excluding batch and caching discounts. Bold indicates the better figure where one is objectively better. Values we could not confirm from the provider are shown as “Not verified” rather than estimated.

Benchmark receipts

Where each score comes from, and how far it can be compared across models.

  • 2026-09-26
    Artificial Analysis (Reasoning, AA-estimated)

    Composite index blending reasoning, knowledge, and coding evals into one 0–100 score.

    Comparable with caveatOnly same-version scores are comparable. v4.3.2 was rebaselined (the top score fell from 66 on v4.1.1 to ~58), so v4.1.1 figures must not be compared with v4.3.2 figures — check measuredAt.

Pricing tiers

GLM 5.2: Z.ai's per-token table lists $1.40/$4.40 per MTok (same list as 5.3). Open-weight, text-only; 1M context, 128K max output per Z.ai docs.

Qwen3-235B-A22B: Model Studio International $0.70 input / $2.80 output per MTok (non-thinking); thinking-mode output $8.40. Open weights (Apache 2.0) for self-hosting; 32,768-token recommended output.

BalancedOpen weightsRecord checked September 26, 2026

GLM 5.2

GLM 5.2 is Zhipu's previous-generation open-weight model with strong cost-performance.

Best for

  • Open-weight deployments
  • Reasoning
  • Cost-sensitive work

Watch out

Superseded by GLM 5.3 (Coding Plan 5.2/5.1 requests route to 5.3). Parameter count: sources disagree.

BalancedOpen weightsRecord checked September 26, 2026

Qwen3-235B-A22B

Qwen3-235B-A22B is Alibaba's widely deployed open-weight MoE — 235B/22B, strong price-performance.

Best for

  • Open-weight deployments
  • Self-hosting
  • Multilingual

Watch out

Needs multi-GPU for the 235B total; hosted rates vary.

When the cheaper one wins

Qwen3-235B-A22B is cheaper on output at $2.80 per million tokens against $4.40 for GLM 5.2 — about 1.6×. Use the cheaper tier for classification, extraction, summarisation, and any task where the expensive model’s extra score does not change the accepted output. The expensive one only pays if your hardest task actually fails on the cheap tier. These are standard-tier API rates, excluding batch and cache discounts.

Run the model picker

Evidence confidence: High

How strong and complete the evidence behind this comparison is — not a prediction of which model is better.

  • Pricing verified on both sides — Input and output rates are verified for both models.
  • 5/5 core specs verified on both sides — All core specifications verified for both models.
  • 1 shared named benchmark with differing scores — Measured on: Artificial Analysis Intelligence Index.
  • Verified within the last 90 days — Newest catalog check was 2 days ago.
  • Both models carry source citations — Each side has at least two catalog sources on record.

Source receipts

Each catalog figure was checked against the provider or an independent second source on the date shown.

Related comparisons

Diving deeper on one model? GLM 5.2 · Qwen3-235B-A22B

Common questions

GLM 5.2 vs Qwen3-235B-A22B

Answered from the verified figures on this page rather than general guidance.

Is GLM 5.2 or Qwen3-235B-A22B cheaper for input?
Qwen3-235B-A22B is cheaper at $0.70 per million input tokens, against $1.40 for GLM 5.2 — roughly 2.0× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; GLM 5.2 has tiered pricing: Z.ai's per-token table lists $1.40/$4.40 per MTok (same list as 5.3). Open-weight, text-only; 1M context, 128K max output per Z.ai docs. Qwen3-235B-A22B has tiered pricing: Model Studio International $0.70 input / $2.80 output per MTok (non-thinking); thinking-mode output $8.40. Open weights (Apache 2.0) for self-hosting; 32,768-token recommended output.
Is GLM 5.2 or Qwen3-235B-A22B cheaper for output?
Qwen3-235B-A22B is cheaper at $2.80 per million output tokens, against $4.40 for GLM 5.2 — roughly 1.6× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; GLM 5.2 has tiered pricing: Z.ai's per-token table lists $1.40/$4.40 per MTok (same list as 5.3). Open-weight, text-only; 1M context, 128K max output per Z.ai docs. Qwen3-235B-A22B has tiered pricing: Model Studio International $0.70 input / $2.80 output per MTok (non-thinking); thinking-mode output $8.40. Open weights (Apache 2.0) for self-hosting; 32,768-token recommended output.
Which has the larger context window, GLM 5.2 or Qwen3-235B-A22B?
GLM 5.2 accepts 1M tokens against 128K for Qwen3-235B-A22B. This only matters if you routinely send very long documents or large codebases.
Do GLM 5.2 and Qwen3-235B-A22B support the same reasoning levels?
Yes — both accept the same effort settings: "low", "high", "max". Higher effort costs more and takes longer, so start low and raise it only where output quality actually improves.
Should I use GLM 5.2 or Qwen3-235B-A22B?
Both sit in the balanced tier, so the choice usually comes down to price and context rather than capability. GLM 5.2 suits open-weight deployments; Qwen3-235B-A22B suits open-weight deployments.

Next step

Choosing between them

The verified figures that separate this pair, computed from the catalog rather than restated boilerplate.

  • Input price: Qwen3-235B-A22B costs $0.70 per 1M tokens versus $1.40 for GLM 5.2 — a 2x difference at the headline tier.
  • Context: GLM 5.2 takes 1M against 128K for Qwen3-235B-A22B — only decisive if your prompts approach the smaller window.
Run the model pickerEstimate stack costAll model comparisons

Choosing a harness rather than a model — Cursor, Copilot, Claude Code, Windsurf, or Lovable? Compare agentic harnesses · Latest releases.