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Model comparison

GLM 5.3 Flash vs GPT-5.2

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

Catalog record checked September 3, 2026Individual provider fields may changeEvidence confidence: High — see receipts below

Z.ai

GLM 5.3 Flash

Balanced · Open weights

vs

OpenAI

GPT-5.2

Balanced

AI model capability comparison
SpecificationGLM 5.3 FlashGPT-5.2
ProviderZ.aiOpenAI
TierBalancedBalanced
Context windowWinner: 1.05M400K
Max outputWinner: 131K128K
Input / 1M tokensWinner: $0.15$1.75
Output / 1M tokensWinner: $0.50$14
WeightsOpenClosed
Parameters320B total / 18B active (MoE)Not disclosedUnverified
Reasoning levelsNot verifiedUnverifiednone, low, medium, high, xhigh, max
Modalitiestext, image, videotext, image
LicenseMITNot disclosedUnverified
API model idNot publishedUnverifiedgpt-5.2
ReleasedAugust 26, 2026December 11, 2025
Artificial Analysis Intelligence Index (2026-08-26)57Not verifiedUnverified
Artificial Analysis Intelligence Index [high] (2026-08-14)Not verifiedUnverified50
SWE-bench Verified (2026-09-01)92Not verifiedUnverified
Terminal-Bench 2.1 (2026-08)84.3Not verifiedUnverified
DeepSWE 1.1 (2026-08)63.4Not verifiedUnverified
Humanity's Last Exam (2026-08)55.3Not verifiedUnverified

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

  • 2026-09-01: vals.ai SWE-bench Verified leaderboard (independent, mini-swe-agent bash-only); not published by Z.aiReal GitHub issue resolution: does the model's patch pass the hidden tests. Comparability: comparable with caveat — Post-audit vendor claims and pre-audit scores sit on different task trust levels; scaffolding (agent harness, compute budget) also dominates results. Never aggregate across scaffolds.
  • 2026-08-14: Artificial AnalysisComposite index blending reasoning, knowledge, and coding evals into one 0–100 score. Comparability: directly comparable — AA occasionally rebaselines the index scale between snapshots — a score captured on one date is only comparable to same-snapshot scores (check measuredAt).
  • 2026-08: Z.ai GLM-5.3-Flash blog (vendor, mini-swe-agent, 400K context)Agentic software engineering: pass@1 on real repo tasks with reported cost per completed task. Comparability: directly comparable
  • 2026-08: GLM-5.3-Flash HF model card (vendor, with tools, full set)Agentic terminal work: multi-step tasks executed in a sandboxed shell environment. Comparability: comparable with caveat — Scores across Terminal-Bench major versions (v1 vs v2) are NOT comparable; harness configuration (container, time limits) also shifts results.

Pricing tiers: GLM 5.3 Flash: $0.15/$0.50 per MTok is the standard first-party and third-party rate (Z.ai docs; GMI, Novita, Together). A 50% promo tier runs $0.075/$0.25 — confirm which rate your account quotes. · GPT-5.2: Standard $1.75/$14 per MTok; cached input $0.175/MTok; batch $0.875/$7. (gpt-5.2-pro exists at $21/$168.)

BalancedOpen weightsRecord checked September 3, 2026

GLM 5.3 Flash

GLM 5.3 Flash is Z.ai's natively multimodal open-weight workhorse — 1M context, hybrid sparse/linear attention, near-flagship Intelligence Index at a fraction of the cost.

Best for

  • Cost-efficient long-context
  • Multimodal input
  • Coding agents

Watch out

Self-hosting needs ~186GB GPU memory at 4-bit (multi-GPU). Third-party hosts charge more than Z.ai's own API.

BalancedRecord checked September 3, 2026

GPT-5.2

GPT-5.2 was OpenAI's previous flagship — still a strong, widely integrated general model at $1.75/$14.

Best for

  • General production
  • Agentic workflows
  • Knowledge work

Watch out

Two generations behind GPT-5.6; capable but no longer flagship.

When the cheaper one wins

GLM 5.3 Flash is cheaper on output at $0.50 per million tokens against $14 for GPT-5.2 — about 28×. 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.
  • 3/5 core specs verified on both sides — Not published for at least one side: parameter count, reasoning levels.
  • 1 shared named benchmark with differing scores — Measured on: Artificial Analysis Intelligence Index.
  • Verified within the last 90 days — Newest catalog check was 8 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 5.3 Flash · GPT-5.2

Common questions

GLM 5.3 Flash vs GPT-5.2

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

Is GLM 5.3 Flash or GPT-5.2 cheaper for input?

GLM 5.3 Flash is cheaper at $0.15 per million input tokens, against $1.75 for GPT-5.2 — roughly 12× 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 5.3 Flash has tiered pricing: $0.15/$0.50 per MTok is the standard first-party and third-party rate (Z.ai docs; GMI, Novita, Together). A 50% promo tier runs $0.075/$0.25 — confirm which rate your account quotes. GPT-5.2 has tiered pricing: Standard $1.75/$14 per MTok; cached input $0.175/MTok; batch $0.875/$7. (gpt-5.2-pro exists at $21/$168.)

Is GLM 5.3 Flash or GPT-5.2 cheaper for output?

GLM 5.3 Flash is cheaper at $0.50 per million output tokens, against $14 for GPT-5.2 — roughly 28× 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 5.3 Flash has tiered pricing: $0.15/$0.50 per MTok is the standard first-party and third-party rate (Z.ai docs; GMI, Novita, Together). A 50% promo tier runs $0.075/$0.25 — confirm which rate your account quotes. GPT-5.2 has tiered pricing: Standard $1.75/$14 per MTok; cached input $0.175/MTok; batch $0.875/$7. (gpt-5.2-pro exists at $21/$168.)

Which has the larger context window, GLM 5.3 Flash or GPT-5.2?

GLM 5.3 Flash accepts 1.05M tokens against 400K for GPT-5.2. This only matters if you routinely send very long documents or large codebases.

Should I use GLM 5.3 Flash or GPT-5.2?

Both sit in the balanced tier, so the choice usually comes down to price and context rather than capability. GLM 5.3 Flash suits cost-efficient long-context; GPT-5.2 suits general production.

Can I self-host GLM 5.3 Flash or GPT-5.2?

GLM 5.3 Flash publishes open weights, but self-hosting and third-party provider access depend on the licence, hardware, serving support, and availability. GPT-5.2 is a closed model whose supported access paths are controlled by its provider.

Next step

Choosing between them

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

  • Input price: GLM 5.3 Flash costs $0.15 per 1M tokens versus $1.75 for GPT-5.2 — a 11.7x difference at the headline tier.
  • Context: GLM 5.3 Flash takes 1.05M against 400K for GPT-5.2 — only decisive if your prompts approach the smaller window.
  • Measured capability: GLM 5.3 Flash leads Artificial Analysis Intelligence Index 57 to 50 (measured 2026-08-26).
  • Deployment: GLM 5.3 Flash publishes weights you can self-host; the other is API-only.
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