[Overview](#overview)
[GLM 5.3](https://z.ai/blog/glm-5.3) arrives today with day-0 serving support
from Inco AI on
[TokenRouter](https://www.tokenrouter.com/) compute. The
release pairs [Z.ai's](https://z.ai/) new model with our core inference
optimization technology:
- A DFlash 2 checkpointfor speculative decoding. - An NVFP4 checkpointfor efficient Blackwell inference with native accuracy. Inco Enginefor end-to-end inference performance.
As a day-0 launch partner, we are releasing both checkpoints alongside the model endpoint. Together, the checkpoints and Inco Engine deliver up to 4.4× throughput versus the native FP8 checkpoint with autoregressive decoding at concurrency 1.
[DFlash 2 for GLM 5.3](#dflash-2-for-glm-53)
[DFlash 2](/blog/dflash2/) is a parallel drafter for speculative decoding: it
predicts candidate tokens in one pass and lets the target model verify them as a block.
Acceptance length (AL) measures how many tokens each draft–verify cycle yields, including the verifier's next token. A longer accepted block means fewer full target-model passes for the same output. DFlash 2 improves AL by keeping the parallel draft design while selecting a more coherent path through each position's candidates.
Acceptance length is only half of the serving result: a drafter also adds work to each cycle. For GLM 5.3, we therefore report end-to-end decode throughput separately, comparing the model's native MTP path and DFlash 2 against autoregressive decoding. At concurrency 1, DFlash 2 reaches 383.3 output tok/s on MATH-500, 366.6 on GSM8K, and 363.7 on HumanEval.
NVFP4 for Blackwell We are also releasing an NVFP4 checkpoint for efficient Blackwell deployment, with accuracy matching the native FP8 checkpoint across the evaluation suite.
| Precision | GPQA Diamond | AIME 2025 | MATH-500 | HLE | AA-LCR |
|---|---|---|---|---|---|
| FP8 | 91.1 | 94.3 | 95.6 | 35.9 | 73.6 |
| NVFP4 | 91.2 | 95.1 | 95.2 | 35.2 | 73.0 |
[Get access](#get-access)
Try GLM 5.3 in the browser or connect through the Inco API.
Included in preview
-
Browser playground
-
OpenAI and Anthropic API dialects
-
Streaming responses
-
1M-token context window
List pricing
per 1M tokens- Input
- $1.40
- Cached input
- $0.26
- Output
- $4.40
[Get checkpoints](#get-checkpoints)
[Compute for GLM 5.3](#compute-for-glm-53)
Compute for this launch came from TokenRouter. We trained the DFlash 2 drafter and produced the NVFP4 checkpoint on its Blackwell clusters, and we serve the day-0 endpoint from the same pool. You can reach the endpoint with an existing TokenRouter key.
[The bottom line](#the-bottom-line)
Ten days ago, we called [DFlash 2](/blog/dflash2/) the first piece of an
end-to-end serving stack. Launches like this are what the rest of it is for.
GLM 5.3 shipped today, and the stack shipped with it: a DFlash 2 drafter, an NVFP4 checkpoint, and a live endpoint on Inco Engine. Together they serve the model at up to 4.4× the throughput of the native FP8 checkpoint with autoregressive decoding, measured at concurrency 1.
If you want your model served like this, fine-tunes included, write to us:
[contact@inco.ai](mailto:contact@inco.ai).
[Get updates](#get-updates)
One email when we ship something new.
We will never share your email address.