It turns out that the outrageously popular free stealth model OxAlpha was actually https://openrouter.ai/z-ai/glm-5.3-flash

(see https://www.linkedin.com/posts/phildour_glm-53-flash-just-came-out-of-stealth-it-activity-7498468815823933441-Gse3)

This model beats Opus 4.8 on most benchmarks, and if you've seen anything about OxAlpha, it is extremely capable in most ways that matter. You can use it yourself right now in Pi for only $0.075/$0.25 per million tokens in/out. Paste this prompt into Pi to add it :

Please add to pi the z-ai/glm-5.3-flash model from the openrouter provider. Please set the context length to 1 million tokens and the output length to the max allowable

The only other near-frontier model which competes with it in price is meta/muse-spark-1.2-contributor ($0.10/$0.20 per million tokens in/out) - that is the same model as meta/muse-spark-1.2, but you must agree to let Meta train on any data you enter into the contributor version, and it requires signing an 18 years old or older agreement.

You can run GLM 5.3 Flash locally!

The really exciting thing about GLM 5.3 Flash is that it will run on 2 clustered DGX Spark machines, at a 4 bit quant, with enough VRAM to spare for a large KV cache. And it should run quickly, at something like 40 tokens per second, using the built-in ConnectX-7 link configured with RoCE v2 (running in vLLM with Ray).

Stay tuned for my tests!

It turns out that the outrageously popular free stealth model OxAlpha was actually https://openrouter.ai/z-ai/glm-5.3-flash

See:

https://www.linkedin.com/posts/phildour_glm-53-flash-just-came-out-of-stealth-it-activity-7498468815823933441-Gse3

This model beats Opus 4.8 on most benchmarks, and if you've seen anything about OxAlpha, it is extremely capable in most ways that matter. You can use it yourself right now in Pi for only $0.075/$0.25 per million tokens in/out. Paste this prompt into Pi to add it :

Please add to pi the z-ai/glm-5.3-flash model from the openrouter provider. Please set the context length to 1 million tokens and the output length to the max allowable

The only other near-frontier model which competes with it in price is meta/muse-spark-1.2-contributor ($0.10/$0.20 per million tokens in/out) - that is the same model as meta/muse-spark-1.2, but you must agree to let Meta train on any data you enter into the contributor version, and it requires signing an 18 years old or older agreement.

You can run it locally!

The really exciting thing about GLM 5.3 Flash is that it will run on 2 clustered DGX Spark machines, at a 4 bit quant, with enough VRAM to spare for the full million token context limit. And it should run fast, at something like 40 tokens per second, using the built-in ConnectX-7 link configured with RoCE v2 (plan on running in vLLM with Ray).

Stay tuned for my tests!