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
| Provider | Quantization | Input / 1M | Output / 1M | Cache read / 1M | Context | p50 latency | p50 throughput | Uptime (1d) |
|---|---|---|---|---|---|---|---|---|
| Open Inference | fp4 | $0.0261 / 1M | $0.9 / 1M | $0.0108 / 1M | 1,048,576 tokens | 3.88 s | 19 tok/s | 99.34% |
| Relace | unknown | $0.04 / 1M | $0.5 / 1M | $0.0125 / 1M | 1,048,576 tokens | 1.91 s | 42 tok/s | 98.01% |
| StreamLake | fp8 | $0.0435 / 1M | $0.145 / 1M | $0.0087 / 1M | 1,024,000 tokens | 1.19 s | 39 tok/s | 100.00% |
| Sail Research | fp4 | $0.045 / 1M | $0.6 / 1M | $0.0285 / 1M | 1,048,576 tokens | 1.41 s | 77 tok/s | 98.51% |
| Sail Research | fp4 | $0.045 / 1M | $0.6 / 1M | $0.0285 / 1M | 1,048,576 tokens | 1.36 s | 80 tok/s | 98.51% |
| Reka AI | unknown | $0.06 / 1M | $1.6 / 1M | $0.04 / 1M | 262,144 tokens | 0.77 s | 106 tok/s | 100.00% |
| inference.net | fp4 | $0.07 / 1M | $0.05 / 1M | $0.03 / 1M | 1,048,576 tokens | 0.55 s | 81 tok/s | 100.00% |
| DeepInfra | fp4 | $0.075 / 1M | $0.25 / 1M | $0.015 / 1M | 1,048,576 tokens | 2.38 s | 10.5 tok/s | 0.00% |
| Inceptron | fp8 | $0.0783 / 1M | $0.55 / 1M | $0.099 / 1M | 1,048,576 tokens | 0.73 s | 69 tok/s | 97.68% |
| NovitaAI | fp8 | $0.084 / 1M | $0.28 / 1M | $0.0168 / 1M | 1,048,576 tokens | 2.92 s | 32 tok/s | 100.00% |
| GMICloud | fp8 | $0.09 / 1M | $0.3 / 1M | $0.018 / 1M | 1,048,576 tokens | 4.48 s | 36 tok/s | 93.38% |
| Decart | fp4 | $0.093 / 1M | $0.31 / 1M | $0.0186 / 1M | 1,048,576 tokens | 1.42 s | 52 tok/s | 100.00% |
| NEAR AI | fp8 | $0.105 / 1M | $0.35 / 1M | $0.0245 / 1M | 1,048,576 tokens | 1.47 s | 30 tok/s | 100.00% |
| Phala | nvfp4 | $0.1125 / 1M | $0.375 / 1M | $0.0225 / 1M | 1,048,576 tokens | 3.57 s | 34 tok/s | 100.00% |
| DigitalOcean | unknown | $0.13125 / 1M | $0.4375 / 1M | $0.03 / 1M | 1,048,576 tokens | 0.59 s | 41 tok/s | 100.00% |
| Wafer | unknown | $0.135 / 1M | $0.5 / 1M | $0.012 / 1M | 1,048,576 tokens | 1.12 s | 75 tok/s | 99.67% |
| Modal | nvfp4 | $0.15 / 1M | $0.5 / 1M | $0.03 / 1M | 1,048,576 tokens | 0.31 s | 169 tok/s | 100.00% |
| Baseten | fp8 | $0.15 / 1M | $0.5 / 1M | $0.03 / 1M | 1,048,576 tokens | 0.49 s | 114 tok/s | 100.00% |
| Crusoe | fp4 | $0.15 / 1M | $0.5 / 1M | $0.03 / 1M | 1,048,576 tokens | 0.89 s | 89 tok/s | 100.00% |
| CoreWeave | nvfp4 | $0.15 / 1M | $0.5 / 1M | $0.05 / 1M | 1,048,576 tokens | 0.45 s | 271 tok/s | 97.68% |
| Fireworks | unknown | $0.15 / 1M | $0.5 / 1M | $0.03 / 1M | 1,048,576 tokens | 0.59 s | 128 tok/s | 100.00% |
| Friendli | unknown | $0.15 / 1M | $0.5 / 1M | $0.03 / 1M | 1,048,576 tokens | 0.54 s | 157 tok/s | 100.00% |
| Together | unknown | $0.15 / 1M | $0.5 / 1M | $0.03 / 1M | 1,048,575 tokens | 0.80 s | 130 tok/s | 100.00% |
| Parasail | fp4 | $0.15 / 1M | $0.5 / 1M | $0.03 / 1M | 1,048,576 tokens | 0.81 s | 112 tok/s | 100.00% |
| Baseten | fp8 | $0.15 / 1M | $0.5 / 1M | $0.03 / 1M | 1,048,576 tokens | 0.39 s | 104 tok/s | 100.00% |
| Venice | unknown | $0.15 / 1M | $0.5 / 1M | $0.03 / 1M | 1,048,576 tokens | 0.86 s | 102 tok/s | 100.00% |
| Z.ai | fp8 | $0.15 / 1M | $0.5 / 1M | $0.03 / 1M | 1,048,576 tokens | 3.60 s | 45 tok/s | 100.00% |
| Parasail Fast | fp4 | $0.1875 / 1M | $0.625 / 1M | $0.0375 / 1M | 1,048,576 tokens | 0.96 s | 140 tok/s | 99.67% |
| Fireworks | unknown | $0.225 / 1M | $0.75 / 1M | $0.045 / 1M | 1,048,576 tokens | 0.51 s | 152 tok/s | 100.00% |
| Morph | fp8 | $0.029 / 1M | $1 / 1M | $0.015 / 1M | 1,048,576 tokens | 4.59 s | 10 tok/s | 88.08% |
| AtlasCloud | fp8 | $0.15 / 1M | $0.5 / 1M | $0.03 / 1M | 1,048,576 tokens | 5.24 s | 44 tok/s | 93.60% |
| SiliconFlow | fp8 | $0.15 / 1M | $0.5 / 1M | $0.03 / 1M | 1,048,576 tokens | 1.26 s | 55 tok/s | 90.50% |
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 category | Elo | Win rate | Rank |
|---|---|---|---|
| 3d | 1319 | 56.4% | #14 |
| asciiart | 1268 | 55% | #11 |
| codecategories | 1286 | 49.4% | #19 |
| dataviz | 1264 | 50.3% | #28 |
| gamedev | 1287 | 47.3% | #20 |
| svg | 1288 | 57% | #10 |
| uicomponent | 1323 | 54.9% | #11 |
| website | 1275 | 48.5% | #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.
| Provider | GPQA Diamond | TAU-Bench Airline | Runs |
|---|---|---|---|
| AtlasCloud | 84.24% | 75.98% | 4 |
| auto-routing | 83.87% | 76.11% | 5 |
| Baseten | 82.84% | 75.17% | 5 |
| Baseten | 83.28% | — | 5 |
| Cloudflare | 82.55% | 73.76% | 4 |
| CoreWeave | 81.72% | 75.83% | 5 |
| Crusoe | 83.14% | 75.55% | 5 |
| Decart | 82.75% | 73.99% | 4 |
| DeepInfra | 89.27% | 75.77% | 4 |
| DekaLLM | 85.32% | 76.73% | 4 |
| DigitalOcean | 84.05% | 72.51% | 6 |
| Fireworks | 84.52% | 75.33% | 5 |
| Fireworks | 84.32% | 75.84% | 3 |
| Friendli | 83.24% | 74.37% | 5 |
| GMICloud | 87.51% | 74.38% | 5 |
| Inceptron | 86.65% | 74.97% | 5 |
| inference.net | 85.49% | 75.22% | 7 |
| io.net | 86.22% | 74.25% | 7 |
| Makora | 86.2% | 72.22% | 1 |
| Modal | 82.06% | 71.07% | 2 |
| Modal | 82.59% | 76.36% | 4 |
| Morph | 82.04% | 74.12% | 7 |
| NEAR AI | 85.39% | 77.74% | 6 |
| NextBit | 82.29% | 75.73% | 6 |
| NovitaAI | 83.33% | 76.41% | 5 |
| Open Inference | 80.91% | 71.71% | 8 |
| Parasail | 83.15% | 74.82% | 5 |
| Parasail Fast | 80.89% | 78.64% | 2 |
| Phala | 87.44% | 76.07% | 5 |
| Prime Intellect | 82.49% | 74% | 1 |
| Reka AI | 83.28% | 74.28% | 8 |
| Relace | 83.46% | 77.43% | 6 |
| Sail Research | 80.59% | 75.46% | 5 |
| Sail Research | 81.99% | 74.4% | 5 |
| SiliconFlow | 83.96% | 77.29% | 5 |
| StreamLake | 83.27% | 75.85% | 6 |
| Together | 83.78% | 73.84% | 5 |
| Venice | 88.07% | 77.17% | 5 |
| Wafer | 87.07% | 77.03% | 8 |
| Z.ai | 87.79% | 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
- GLM 5.3 Flash third-party catalog record (catalog, checked 2026-10-13)
- Third-party model catalog methodology (methodology, checked 2026-10-13)
- Z.ai official model documentation (primary, checked 2026-10-13)
- Artificial Analysis capability indices methodology (benchmark, checked 2026-10-13)
- Design Arena leaderboard and methodology (benchmark, checked 2026-10-13)
- GLM 5.3 Flash third-party catalog record (benchmark, checked 2026-10-13)
- GLM 5.3 Flash provider or route reference (primary, checked 2026-10-13)