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AI Choice Engine

Model comparison

GLM 5.2 vs Grok 4.5

Z.ai against SpaceXAI, compared on context, price, and attributed benchmark results.

Recorded profile verification October 2, 2026Individual provider fields may changeEvidence confidence: Medium — see receipts below

Z.ai

GLM 5.2

Balanced · Open weights

vs

SpaceXAI

Grok 4.5

Balanced

AI model capability comparison
SpecificationGLM 5.2Grok 4.5
ProviderZ.aiSpaceXAI
TierBalancedBalanced
Context windowWinner: 1M500K
Max output131KNot verifiedUnverified
Input / 1M tokensWinner: $1.40$2
Output / 1M tokensWinner: $4.40$6
WeightsOpenClosed
ParametersNot verifiedUnverifiedNot verifiedUnverified
Reasoning levelsnone, minimal, low, medium, high, xhigh, maxlow, medium, high
Modalitiestexttext, image
LicenseMITNot verifiedUnverified
API model idglm-5.2grok-4.5
ReleasedJune 16, 2026July 8, 2026
Terminal-Bench 2.1 · source date Grok 4.5: 2026-07-16Not verifiedUnverified83.3
DeepSWE 1.1 · source date Grok 4.5: 2026-07-16Not verifiedUnverified53
DeepSWE 1.1 · source date Grok 4.5: 2026-07Not verifiedUnverified54

Dates beside benchmark scores refer to the linked source’s publication or capture date unless that source explicitly states when it measured the result. A shared URL alone does not establish comparable runs; unverified setups are marked. Prices are USD per million tokens at standard rates, excluding batch and caching discounts. 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.

Pricing tiers

GLM 5.2: Z.ai token API $1.40/$4.40 per MTok, cached input $0.26; cache storage is limited-time free with no verified end date. Text-only API advertises 1M context and a 131,072 output ceiling. The MIT checkpoint config sets 1,048,576 native context.

Grok 4.5: Standard $2/$6 per MTok below 200K prompt tokens; at 200K or more the full request bills $4/$12. Cached input $0.30 short or $0.60 long. US regional inference adds 10%. No separate text-output cap is verified.

BalancedOpen weightsRecord checked October 2, 2026

GLM 5.2

The previous GLM text-only generation, available as an MIT-licensed checkpoint and documented token-API model; GLM-5.3 uses the same base with newer post-training.

Best for

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

Watch out

Coding Plan 5.2 requests route to 5.3; direct token-API identity is separate. GLM-5.2 supports thinking on/off: none/minimal stop thinking, low/medium map to high, and xhigh maps to max (default). Accepted effort strings do not represent seven independent compute tiers. Exact total/active parameter counts remain unverified; do not infer them solely from the shared base.

BalancedRecord checked October 1, 2026

Grok 4.5

Grok 4.5 is SpaceXAI's hosted reasoning model with a 500K-token context and configurable low, medium and high effort.

Best for

  • Real-time data queries
  • Technical tasks
  • Cost-sensitive reasoning

Watch out

An earlier API model, still listed in pricing; current docs recommend Grok 4.7. Context is 500K. xhigh requests map to high and reasoning cannot be disabled; presencePenalty, frequencyPenalty and stop are unsupported. Match the exact model, effort and dated benchmark configuration.

When the cheaper one wins

GLM 5.2 is cheaper on output at $4.40 per million tokens against $6 for Grok 4.5 — about 1.4×. 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. On DeepSWE 1.1, GLM 5.2 is 43.8% Pass@1 at $3.92/task versus Grok 4.5 at 53.8% / $2.42/task. This compares standard short-context token rates, not total cost per accepted task. Include input, cache, context tiers, schedules, retries and review in your pilot.

Run the model picker

Evidence confidence: Medium

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: max output, parameter count.
  • No directly aligned benchmark setup — No benchmark has matching cited sources, source dates, units, effort and recorded run details on both models.
  • Verified within the last 90 days — Older of the two catalog checks was 25 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 · Grok 4.5

Common questions

GLM 5.2 vs Grok 4.5

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

Is GLM 5.2 or Grok 4.5 cheaper for input?
GLM 5.2 is cheaper at $1.40 per million input tokens, against $2 for Grok 4.5 — roughly 1.4× the price. Estimate both input and output token volume for your workload. These are base rates; GLM 5.2: Z.ai token API $1.40/$4.40 per MTok, cached input $0.26; cache storage is limited-time free with no verified end date. Text-only API advertises 1M context and a 131,072 output ceiling. The MIT checkpoint config sets 1,048,576 native context. Grok 4.5: Standard $2/$6 per MTok below 200K prompt tokens; at 200K or more the full request bills $4/$12. Cached input $0.30 short or $0.60 long. US regional inference adds 10%. No separate text-output cap is verified.
Is GLM 5.2 or Grok 4.5 cheaper for output?
GLM 5.2 is cheaper at $4.40 per million output tokens, against $6 for Grok 4.5 — roughly 1.4× the price. Estimate both input and output token volume for your workload. These are base rates; GLM 5.2: Z.ai token API $1.40/$4.40 per MTok, cached input $0.26; cache storage is limited-time free with no verified end date. Text-only API advertises 1M context and a 131,072 output ceiling. The MIT checkpoint config sets 1,048,576 native context. Grok 4.5: Standard $2/$6 per MTok below 200K prompt tokens; at 200K or more the full request bills $4/$12. Cached input $0.30 short or $0.60 long. US regional inference adds 10%. No separate text-output cap is verified.
Which has the larger context window, GLM 5.2 or Grok 4.5?
GLM 5.2 accepts 1M tokens against 500K for Grok 4.5. This only matters if you routinely send very long documents or large codebases.
Do GLM 5.2 and Grok 4.5 support the same reasoning levels?
GLM 5.2 exposes none, minimal, low, medium, high, xhigh, max, while Grok 4.5 exposes low, medium, high.
Should I use GLM 5.2 or Grok 4.5?
Both are classified in our balanced tier; this editorial grouping does not imply equal capability. GLM 5.2 is a candidate for open-weight deployments; Grok 4.5 is a candidate for real-time data queries. Compare accuracy, tool reliability, latency and cost on representative tasks.
Can I self-host GLM 5.2 or Grok 4.5?
GLM 5.2 publishes open weights, but self-hosting and third-party provider access depend on the licence, hardware, serving support, and availability. Grok 4.5 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 5.2 costs $1.40 per 1M tokens versus $2 for Grok 4.5 — a 1.4x difference at the headline tier.
  • Context: GLM 5.2 takes 1M against 500K for Grok 4.5 — only decisive if your prompts approach the smaller window.
  • Deployment: GLM 5.2 publishes weights you can self-host; the other is API-only.
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