GLM 5.3 Flash API model profile

Evidence snapshot:

GLM 5.3 Flash is a Z.ai model profile with a 1,000,000-token context window. The dated catalog snapshot records text, image, video modalities and interfaces for prompt caching, reasoning controls, structured output, text, text generation.

GLM-5.3-Flash is a native multimodal model from Z.ai. It is suited for efficient coding and long-horizon agent tasks. Its hybrid sparse and linear attention architecture maintains accurate long-context behavior while reducing compute overhead.

GLM 5.3 Flash is worth reaching for when you need a route priced in the cheapest quarter of the catalog and scoring in the top quarter on the published intelligence index. The conditions below are the ones its own numbers support.

GLM 5.3 Flash is available under the Kendr alias kc-glm-5.3-flash. Current account availability and customer credit quotes come from Kendr's live public model API and applicable account policy.

GLM 5.3 Flash accepts text, image, and video and returns text. The snapshot records prompt caching, reasoning controls, structured output, text, text generation, tool calling, video input, vision, and web search as capabilities or interfaces.

The dated reference snapshot lists $0.0261 input and $0.05 output per million tokens. Cached input is $0.0087 per million tokens. The separately published provider-route reference is $0.07 / $0.25 ($0.02/M cached input).

The 2026-10-13 snapshot includes 3 Artificial Analysis indexes, 8 Design Arena categories, and AutoExacto results for 40 provider observations. Publisher-reported launch results are labeled and are not presented as Kendr measurements; scores from different suites are not treated as interchangeable.

GLM 5.3 Flash ranked #2 in the cited trailing-7-day third-party catalog usage dataset as of 2026-10-13. Observed within the cited trailing-7-day third-party catalog usage dataset; this is not global AI market share.

Profile data was reviewed for the 2026-10-13 snapshot. Claims retain their source dates, and unavailable fields are shown as unavailable instead of estimated.

Profile facts

Profile type
Kendr API model
Kendr API alias
kc-glm-5.3-flash
Model developer
Z.ai
Kendr route provider
Z.AI
Context window
1M
Snapshot date
2026-10-13
Knowledge cutoff
Not disclosed
Reference catalog ID
z-ai/glm-5.3-flash

When to pick GLM 5.3 Flash

GLM 5.3 Flash is worth reaching for when you need a route priced in the cheapest quarter of the catalog and scoring in the top quarter on the published intelligence index. The conditions below are the ones its own numbers support.

Each condition below is derived from this model's own values in the 2026-10-13 snapshot, compared only against models publishing the same field.

  • Reach for it when cost is the binding constraint. At $0.026 in and $0.05 out per 1M tokens, combined token price sits in the cheapest quarter of the 149 models publishing both rates in this snapshot.
  • Reach for it when answer quality matters more than unit cost. It scores 41.8 on the Artificial Analysis intelligence index, above three quarters of the 119 models carrying that field in the 2026-10-13 snapshot.
  • Reach for it when the input includes images. The snapshot records image input, so screenshots, scans, and diagrams can be sent directly instead of described.
  • Reach for it when the model has to call tools. Tool calling is recorded in the snapshot, so this route can drive an agent loop rather than only answer in prose.
  • Look elsewhere when the request is trivial and latency-sensitive. Reasoning is mandatory on this route and cannot be turned off, so short factual requests still pay reasoning tokens and reasoning latency.

Context, modalities, and identity

GLM 5.3 Flash accepts text, image, and video and returns text. The snapshot records prompt caching, reasoning controls, structured output, text, text generation, tool calling, video input, vision, and web search as capabilities or interfaces.

Model developer
Z.ai
Kendr route provider
Z.AI
Context window
1M
Maximum output
943,718 tokens
Input modalities
text, image, and video
Output modalities
text
Knowledge cutoff
Not disclosed

Model overview

GLM-5.3-Flash is a native multimodal model from Z.ai. It is suited for efficient coding and long-horizon agent tasks. Its hybrid sparse and linear attention architecture maintains accurate long-context behavior while reducing compute overhead.

Reference model ID
z-ai/glm-5.3-flash
Canonical version
z-ai/glm-5.3-flash-20260826
Hugging Face ID
zai-org/GLM-5.3-Flash

Capabilities and supported controls

Capabilities and parameters are reported from the dated catalog and source records; their presence does not guarantee identical behavior across every provider route.

Supported parameters
frequency_penalty, include_reasoning, logit_bias, logprobs, max_tokens, min_p, parallel_tool_calls, presence_penalty, reasoning, reasoning_effort, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_k, top_logprobs, top_p
  • prompt caching
  • reasoning controls
  • structured output
  • text
  • text generation
  • tool calling
  • video input
  • vision
  • web search

Dated pricing snapshot

The dated reference snapshot lists $0.0261 input and $0.05 output per million tokens. Cached input is $0.0087 per million tokens. The separately published provider-route reference is $0.07 / $0.25 ($0.02/M cached input).

Reference figures are dated 2026-10-13; the live Kendr quote can differ by selected provider route, context tier, caching, tools, region, and current rate card.

Price date
2026-10-13
Input
$0.0261 per 1M tokens
Cached input
$0.0087 per 1M tokens
Output
$0.05 per 1M tokens

Provider routes, performance, and uptime

The snapshot retains 32 provider endpoints. Provider prices, context limits, p50 performance, and uptime can differ by route and are not Kendr guarantees.

Active provider endpoints
29
Best p50 latency
0.31 s
Best p50 throughput
271 tok/s
Availability with routing
99.91% over the sampled window
Availability without routing
96.03% over the sampled window
Performance date
2026-10-13
ProviderQuantizationInput / 1MOutput / 1MCache read / 1MContextp50 latencyp50 throughputUptime (1d)
Open Inferencefp4$0.0261 / 1M$0.9 / 1M$0.0108 / 1M1,048,576 tokens3.88 s19 tok/s99.34%
Relaceunknown$0.04 / 1M$0.5 / 1M$0.0125 / 1M1,048,576 tokens1.91 s42 tok/s98.01%
StreamLakefp8$0.0435 / 1M$0.145 / 1M$0.0087 / 1M1,024,000 tokens1.19 s39 tok/s100.00%
Sail Researchfp4$0.045 / 1M$0.6 / 1M$0.0285 / 1M1,048,576 tokens1.41 s77 tok/s98.51%
Sail Researchfp4$0.045 / 1M$0.6 / 1M$0.0285 / 1M1,048,576 tokens1.36 s80 tok/s98.51%
Reka AIunknown$0.06 / 1M$1.6 / 1M$0.04 / 1M262,144 tokens0.77 s106 tok/s100.00%
inference.netfp4$0.07 / 1M$0.05 / 1M$0.03 / 1M1,048,576 tokens0.55 s81 tok/s100.00%
DeepInfrafp4$0.075 / 1M$0.25 / 1M$0.015 / 1M1,048,576 tokens2.38 s10.5 tok/s0.00%
Inceptronfp8$0.0783 / 1M$0.55 / 1M$0.099 / 1M1,048,576 tokens0.73 s69 tok/s97.68%
NovitaAIfp8$0.084 / 1M$0.28 / 1M$0.0168 / 1M1,048,576 tokens2.92 s32 tok/s100.00%
GMICloudfp8$0.09 / 1M$0.3 / 1M$0.018 / 1M1,048,576 tokens4.48 s36 tok/s93.38%
Decartfp4$0.093 / 1M$0.31 / 1M$0.0186 / 1M1,048,576 tokens1.42 s52 tok/s100.00%
NEAR AIfp8$0.105 / 1M$0.35 / 1M$0.0245 / 1M1,048,576 tokens1.47 s30 tok/s100.00%
Phalanvfp4$0.1125 / 1M$0.375 / 1M$0.0225 / 1M1,048,576 tokens3.57 s34 tok/s100.00%
DigitalOceanunknown$0.13125 / 1M$0.4375 / 1M$0.03 / 1M1,048,576 tokens0.59 s41 tok/s100.00%
Waferunknown$0.135 / 1M$0.5 / 1M$0.012 / 1M1,048,576 tokens1.12 s75 tok/s99.67%
Modalnvfp4$0.15 / 1M$0.5 / 1M$0.03 / 1M1,048,576 tokens0.31 s169 tok/s100.00%
Basetenfp8$0.15 / 1M$0.5 / 1M$0.03 / 1M1,048,576 tokens0.49 s114 tok/s100.00%
Crusoefp4$0.15 / 1M$0.5 / 1M$0.03 / 1M1,048,576 tokens0.89 s89 tok/s100.00%
CoreWeavenvfp4$0.15 / 1M$0.5 / 1M$0.05 / 1M1,048,576 tokens0.45 s271 tok/s97.68%
Fireworksunknown$0.15 / 1M$0.5 / 1M$0.03 / 1M1,048,576 tokens0.59 s128 tok/s100.00%
Friendliunknown$0.15 / 1M$0.5 / 1M$0.03 / 1M1,048,576 tokens0.54 s157 tok/s100.00%
Togetherunknown$0.15 / 1M$0.5 / 1M$0.03 / 1M1,048,575 tokens0.80 s130 tok/s100.00%
Parasailfp4$0.15 / 1M$0.5 / 1M$0.03 / 1M1,048,576 tokens0.81 s112 tok/s100.00%
Basetenfp8$0.15 / 1M$0.5 / 1M$0.03 / 1M1,048,576 tokens0.39 s104 tok/s100.00%
Veniceunknown$0.15 / 1M$0.5 / 1M$0.03 / 1M1,048,576 tokens0.86 s102 tok/s100.00%
Z.aifp8$0.15 / 1M$0.5 / 1M$0.03 / 1M1,048,576 tokens3.60 s45 tok/s100.00%
Parasail Fastfp4$0.1875 / 1M$0.625 / 1M$0.0375 / 1M1,048,576 tokens0.96 s140 tok/s99.67%
Fireworksunknown$0.225 / 1M$0.75 / 1M$0.045 / 1M1,048,576 tokens0.51 s152 tok/s100.00%
Morphfp8$0.029 / 1M$1 / 1M$0.015 / 1M1,048,576 tokens4.59 s10 tok/s88.08%
AtlasCloudfp8$0.15 / 1M$0.5 / 1M$0.03 / 1M1,048,576 tokens5.24 s44 tok/s93.60%
SiliconFlowfp8$0.15 / 1M$0.5 / 1M$0.03 / 1M1,048,576 tokens1.26 s55 tok/s90.50%

Benchmark evidence and limitations

The 2026-10-13 snapshot includes 3 Artificial Analysis indexes, 8 Design Arena categories, and AutoExacto results for 40 provider observations. Publisher-reported launch results are labeled and are not presented as Kendr measurements; scores from different suites are not treated as interchangeable.

Third-party catalog fields normalized from the cited model dataset; benchmark methodology and coverage differ by source.

Intelligence Index
41.8
Coding Index
71.5
Agentic Index
50.9
AutoExacto coverage
40 provider observations over 32 days
Design Arena categoryEloWin rateRank
3d131956.4%#14
asciiart126855%#11
codecategories128649.4%#19
dataviz126450.3%#28
gamedev128747.3%#20
svg128857%#10
uicomponent132354.9%#11
website127548.5%#25

AutoExacto provider benchmarks

Rolling provider observations from the cited third-party benchmark view. The lookback is 32 days; GPQA Diamond and TAU-Bench Airline measure different abilities and should not be blended into one score.

ProviderGPQA DiamondTAU-Bench AirlineRuns
AtlasCloud84.24%75.98%4
auto-routing83.87%76.11%5
Baseten82.84%75.17%5
Baseten83.28%—5
Cloudflare82.55%73.76%4
CoreWeave81.72%75.83%5
Crusoe83.14%75.55%5
Decart82.75%73.99%4
DeepInfra89.27%75.77%4
DekaLLM85.32%76.73%4
DigitalOcean84.05%72.51%6
Fireworks84.52%75.33%5
Fireworks84.32%75.84%3
Friendli83.24%74.37%5
GMICloud87.51%74.38%5
Inceptron86.65%74.97%5
inference.net85.49%75.22%7
io.net86.22%74.25%7
Makora86.2%72.22%1
Modal82.06%71.07%2
Modal82.59%76.36%4
Morph82.04%74.12%7
NEAR AI85.39%77.74%6
NextBit82.29%75.73%6
NovitaAI83.33%76.41%5
Open Inference80.91%71.71%8
Parasail83.15%74.82%5
Parasail Fast80.89%78.64%2
Phala87.44%76.07%5
Prime Intellect82.49%74%1
Reka AI83.28%74.28%8
Relace83.46%77.43%6
Sail Research80.59%75.46%5
Sail Research81.99%74.4%5
SiliconFlow83.96%77.29%5
StreamLake83.27%75.85%6
Together83.78%73.84%5
Venice88.07%77.17%5
Wafer87.07%77.03%8
Z.ai87.79%76.45%5

Popularity and market context

GLM 5.3 Flash ranked #2 in the cited trailing-7-day third-party catalog usage dataset as of 2026-10-13. Observed within the cited trailing-7-day third-party catalog usage dataset; this is not global AI market share.

Third-party catalog rank
#2
Global market share
Not inferred
Observation date
2026-10-13

OpenAI-compatible API example

This example applies to the published Kendr alias on this hosted profile. Check the live public catalog before use.

curl https://api.kendr.org/v1/chat/completions \
  -H "Authorization: Bearer $KENDR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"kc-glm-5.3-flash","messages":[{"role":"user","content":"Hello"}]}'

Frequently asked questions

When should I use GLM 5.3 Flash?

GLM 5.3 Flash is worth reaching for when you need a route priced in the cheapest quarter of the catalog and scoring in the top quarter on the published intelligence index. The conditions below are the ones its own numbers support. Reach for it when cost is the binding constraint: At $0.026 in and $0.05 out per 1M tokens, combined token price sits in the cheapest quarter of the 149 models publishing both rates in this snapshot. Reach for it when answer quality matters more than unit cost: It scores 41.8 on the Artificial Analysis intelligence index, above three quarters of the 119 models carrying that field in the 2026-10-13 snapshot. Reach for it when the input includes images: The snapshot records image input, so screenshots, scans, and diagrams can be sent directly instead of described. Reach for it when the model has to call tools: Tool calling is recorded in the snapshot, so this route can drive an agent loop rather than only answer in prose. Look elsewhere when the request is trivial and latency-sensitive: Reasoning is mandatory on this route and cannot be turned off, so short factual requests still pay reasoning tokens and reasoning latency.

What is GLM 5.3 Flash?

GLM 5.3 Flash is a Z.ai model profile with a 1,000,000-token context window. The dated catalog snapshot records text, image, video modalities and interfaces for prompt caching, reasoning controls, structured output, text, text generation.

What context window does GLM 5.3 Flash have?

The dated profile lists 1M of context and up to 943,718 output tokens. Provider routes, variants, and runtime configuration can impose lower effective limits.

What benchmark evidence is available for GLM 5.3 Flash?

The 2026-10-13 snapshot includes 3 Artificial Analysis indexes, 8 Design Arena categories, and AutoExacto results for 40 provider observations. Publisher-reported launch results are labeled and are not presented as Kendr measurements; scores from different suites are not treated as interchangeable. Third-party catalog fields normalized from the cited model dataset; benchmark methodology and coverage differ by source.

What is the Kendr API alias for GLM 5.3 Flash?

Use kc-glm-5.3-flash as the model value. The live public model API and signed-in catalog remain authoritative for route availability and customer credit quotes.

How is GLM 5.3 Flash priced on Kendr?

The dated reference snapshot lists $0.0261 input and $0.05 output per million tokens. Cached input is $0.0087 per million tokens. The separately published provider-route reference is $0.07 / $0.25 ($0.02/M cached input). Kendr applies one 5% markup to configured provider model cost; the live quote and settled routing receipt are authoritative for a request.

Sources and evidence dates

  1. GLM 5.3 Flash third-party catalog record (catalog, checked 2026-10-13)
  2. Third-party model catalog methodology (methodology, checked 2026-10-13)
  3. Z.ai official model documentation (primary, checked 2026-10-13)
  4. Artificial Analysis capability indices methodology (benchmark, checked 2026-10-13)
  5. Design Arena leaderboard and methodology (benchmark, checked 2026-10-13)
  6. GLM 5.3 Flash third-party catalog record (benchmark, checked 2026-10-13)
  7. GLM 5.3 Flash provider or route reference (primary, checked 2026-10-13)