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AI Choice Engine

Model comparison

GLM 5.3 vs Kimi K3

Z.ai against Moonshot AI, 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 5.3

Frontier · Open weights

vs

Moonshot AI

Kimi K3

Frontier · Open weights

AI model capability comparison
SpecificationGLM 5.3Kimi K3
ProviderZ.aiMoonshot AI
TierFrontierFrontier
Context window1MWinner: 1.05M
Max output131KWinner: 1.05M
Input / 1M tokensWinner: $1.40$3
Output / 1M tokensWinner: $4.40$15
WeightsOpenOpen
Parameters753B total (MoE; active count not verified)2.8T total / 104B active (MoE)
Reasoning levelslow, high, maxlow, high, max
Modalitiestexttext, image, video
LicenseGLM-5.3 License (custom)Kimi K3 License (custom)
API model idglm-5.3kimi-k3
ReleasedAugust 14, 2026July 16, 2026
Artificial Analysis Intelligence Index [max] · source date GLM 5.3: 2026-10-0145Not verifiedUnverified
Artificial Analysis Intelligence Index [max] · source date Kimi K3: 2026-10-01Not verifiedUnverified44
Terminal-Bench 2.1 · source date GLM 5.3: 2026-08-1488.2Not verifiedUnverified
Terminal-Bench 2.1 [max] · source date Kimi K3: 2026-10-01Not verifiedUnverified88.3
DeepSWE 1.1 · source date GLM 5.3: 2026-08-1466.9Not verifiedUnverified
Humanity's Last Exam · source date GLM 5.3: 2026-08-1462.5Not verifiedUnverified
Humanity's Last Exam [max] · source date Kimi K3: 2026-10-01Not verifiedUnverified56
GPQA Diamond [max] · source date Kimi K3: 2026-10-01Not verifiedUnverified93.5
SWE-bench Verified · source date Kimi K3: 2026-10-01Not verifiedUnverified93.4

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 5.3: Z.ai token API $1.40/$4.40 per MTok; cached input $0.26. Cache storage is listed as limited-time free, with no verified end date. Coding Plan points are separate: off-peak/weekend calls consume half the standard points. API docs advertise 1M context and specify a 131,072 output ceiling.

Kimi K3: $3/$15 per million input/output tokens; cached input $0.30. Cache writes add $3/MTok for 5-minute TTL or $6/MTok for 1-hour TTL; hits refresh TTL without another write charge. API access requires a successful top-up of at least $1. max_completion_tokens defaults to 131,072 and can be set up to 1,048,576. Kimi K3 uses a custom license; self-hosting has compute costs.

FrontierOpen weightsRecord checked October 2, 2026

GLM 5.3

Z.ai's text-only GLM flagship, with a 753B-total MoE checkpoint and always-enabled reasoning. Published benchmark figures identify particular harnesses and settings.

Best for

  • Coding Plan subscribers
  • Long-horizon coding
  • Chinese + English

Watch out

Custom licence: model-as-a-service operators whose licensee/affiliate aggregate revenue exceeds $10B in any consecutive 12 months require Z.AI security review before commercial use; the definition excludes embedded end-user features/harnesses and mere relays. Keep attribution/permission notices. Reasoning defaults to max; disabling it fails. Accounts that ever subscribed to Coding Plan, including expired subscriptions, currently have Model API access only through the Chat Completions-compatible protocol. Active parameter count and exact initial weight-publication day remain unverified.

FrontierOpen weightsRecord checked October 1, 2026

Kimi K3

Kimi K3 is Moonshot AI's open-weight multimodal 2.8T/104B MoE model with a 1,048,576-token context.

Best for

  • Open-weight frontier work
  • Long-context
  • Multimodal

Watch out

Thinking is always on; preserve complete assistant reasoning/tool history. Vision input requires base64 or ms:// rather than public image URLs, and temperature/top_p/n/penalties are fixed. Current docs discourage production web-search use. The custom licence requires an agreement for Model-as-a-Service businesses above $20M aggregate licensee/affiliate revenue over consecutive 12 months; commercial products above 100M monthly active users or $20M monthly revenue require Kimi K3 UI attribution. Internal use and official/certified serving routes have separate exemptions. July 16 is Kimi Code's release date, distinct from weights publication.

When the cheaper one wins

GLM 5.3 is cheaper on output at $4.40 per million tokens against $15 for Kimi K3 — about 3.4×. 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 5.3 is 69% Pass@1 at $3.99/task versus Kimi K3 at 68.5% / $4.65/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.
  • 5/5 core specs verified on both sides — All core specifications verified for both models.
  • 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 5.3 · Kimi K3

Common questions

GLM 5.3 vs Kimi K3

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

Is GLM 5.3 or Kimi K3 cheaper for input?
GLM 5.3 is cheaper at $1.40 per million input tokens, against $3 for Kimi K3 — roughly 2.1× the price. Estimate both input and output token volume for your workload. These are base rates; GLM 5.3: Z.ai token API $1.40/$4.40 per MTok; cached input $0.26. Cache storage is listed as limited-time free, with no verified end date. Coding Plan points are separate: off-peak/weekend calls consume half the standard points. API docs advertise 1M context and specify a 131,072 output ceiling. Kimi K3: $3/$15 per million input/output tokens; cached input $0.30. Cache writes add $3/MTok for 5-minute TTL or $6/MTok for 1-hour TTL; hits refresh TTL without another write charge. API access requires a successful top-up of at least $1. max_completion_tokens defaults to 131,072 and can be set up to 1,048,576. Kimi K3 uses a custom license; self-hosting has compute costs.
Is GLM 5.3 or Kimi K3 cheaper for output?
GLM 5.3 is cheaper at $4.40 per million output tokens, against $15 for Kimi K3 — roughly 3.4× the price. Estimate both input and output token volume for your workload. These are base rates; GLM 5.3: Z.ai token API $1.40/$4.40 per MTok; cached input $0.26. Cache storage is listed as limited-time free, with no verified end date. Coding Plan points are separate: off-peak/weekend calls consume half the standard points. API docs advertise 1M context and specify a 131,072 output ceiling. Kimi K3: $3/$15 per million input/output tokens; cached input $0.30. Cache writes add $3/MTok for 5-minute TTL or $6/MTok for 1-hour TTL; hits refresh TTL without another write charge. API access requires a successful top-up of at least $1. max_completion_tokens defaults to 131,072 and can be set up to 1,048,576. Kimi K3 uses a custom license; self-hosting has compute costs.
Which has the larger context window, GLM 5.3 or Kimi K3?
Kimi K3 accepts 1.05M tokens against 1M for GLM 5.3. This only matters if you routinely send very long documents or large codebases.
Do GLM 5.3 and Kimi K3 support the same reasoning levels?
Both expose these named effort settings: "low", "high", "max". The same labels do not guarantee equal compute budgets or behavior across providers. Compare quality, latency and cost on your own tasks.
Should I use GLM 5.3 or Kimi K3?
Both are classified in our frontier tier; this editorial grouping does not imply equal capability. GLM 5.3 is a candidate for coding plan subscribers; Kimi K3 is a candidate for open-weight frontier work. Compare accuracy, tool reliability, latency and cost on representative tasks.

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 costs $1.40 per 1M tokens versus $3 for Kimi K3 — a 2.1x difference at the headline tier.
  • Context: Kimi K3 takes 1.05M against 1M for GLM 5.3 — only decisive if your prompts approach the smaller window.
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