An 8-bit MLX conversion (affine, group size 64; mlx-vlm 0.7.6) of h2oai/h2o-lightning-4b v1.2.3, for Apple Silicon. 5.1 GB (4.8 GiB).
Published by NetProjects (Internet Projects Ltd). Not affiliated with H2O.ai.
This is a decision model, not a chat model. It returns a probability for each answer option, not text.
Serve it with the H2O shim, not with
mlx_lm.serveror a plainmlx_vlmgenerate call. The generic "Use this model" snippets Hugging Face shows for MLX models do not return the label probabilities this model is made for. The commands below set it up with H2O's official shim, unmodified, on top of h2o-lightning-mlx, which reads the label log-probabilities with a float32 head, as the original does on vLLM.
JevBench public (231, CLI bb05a33, --adapter typesafe) | |
|---|---|
| this checkpoint | 205 / 231 (48/48 · 71/72 · 86/111) — same as the model card |
| 4-bit build | 207 / 231 (q4) |
| original weights on MLX (bf16) | 204 / 231 |
| vs bf16 on MLX | 229 / 231 answers identical; probability drift mean 0.006, p95 0.019 |
Very close to the original weights (mean probability drift 0.006); the recommended MLX build.
Images. Image input works through the unchanged shim. On H2O's own receipt example this build gives the same answers as the model card shows, and a small generated-image check (counting, colours, reading a table) passed on this build. It is not a reproduction of H2O's image benchmark.
Limits (as for the original): mostly evaluated in English; works best with about 16 answer options or fewer; no explanations and no video input.
git clone https://github.com/internet-projects/h2o-lightning-mlx && cd h2o-lightning-mlx && ./setup.sh
hf download netprojects/h2o-lightning-4b-mlx-q8 --local-dir mlx-q8
MODEL=mlx-q8 ./serve.sh # http://127.0.0.1:8741/v1/systemone
Tested with the shim at H2O revision v1.2.3, and also with H2O's main shim as of 16 October 2026 (205 / 231, same result).
Full precision: use the original weights, h2oai/h2o-lightning-4b, with the same repo and shim. There is no separate bf16 copy here.
Credits: H2O.ai (H2O-Lightning-4B, Apache-2.0), Qwen team (Qwen3.5-4B, Apache-2.0). This conversion is not affiliated with H2O.ai.
An 8-bit MLX conversion (affine, group size 64; mlx-vlm 0.7.6) of h2oai/h2o-lightning-4b v1.2.3, for Apple Silicon. 5.1 GB (4.8 GiB).
Published by NetProjects (Internet Projects Ltd). Not affiliated with H2O.ai.
This is a decision model, not a chat model. It returns a probability for each answer option, not text.
Serve it with the H2O shim, not with
mlx_lm.serveror a plainmlx_vlmgenerate call. The generic "Use this model" snippets Hugging Face shows for MLX models do not return the label probabilities this model is made for. The commands below set it up with H2O's official shim, unmodified, on top of h2o-lightning-mlx, which reads the label log-probabilities with a float32 head, as the original does on vLLM.
JevBench public (231, CLI bb05a33, --adapter typesafe) | |
|---|---|
| this checkpoint | 205 / 231 (48/48 · 71/72 · 86/111) — same as the model card |
| 4-bit build | 207 / 231 (q4) |
| original weights on MLX (bf16) | 204 / 231 |
| vs bf16 on MLX | 229 / 231 answers identical; probability drift mean 0.006, p95 0.019 |
Very close to the original weights (mean probability drift 0.006); the recommended MLX build.
Images. Image input works through the unchanged shim. On H2O's own receipt example this build gives the same answers as the model card shows, and a small generated-image check (counting, colours, reading a table) passed on this build. It is not a reproduction of H2O's image benchmark.
Limits (as for the original): mostly evaluated in English; works best with about 16 answer options or fewer; no explanations and no video input.
git clone https://github.com/internet-projects/h2o-lightning-mlx && cd h2o-lightning-mlx && ./setup.sh
hf download netprojects/h2o-lightning-4b-mlx-q8 --local-dir mlx-q8
MODEL=mlx-q8 ./serve.sh # http://127.0.0.1:8741/v1/systemone
Tested with the shim at H2O revision v1.2.3, and also with H2O's main shim as of 16 October 2026 (205 / 231, same result).
Full precision: use the original weights, h2oai/h2o-lightning-4b, with the same repo and shim. There is no separate bf16 copy here.
Credits: H2O.ai (H2O-Lightning-4B, Apache-2.0), Qwen team (Qwen3.5-4B, Apache-2.0). This conversion is not affiliated with H2O.ai.