serverAppConfigs/serverAppConfigs-docs/LLM/Radiance Model Families.md

---
type: "reference"
title: "Radiance Model Families — arch ids, descriptors and recipes"
description: "Which radiance plugin claims which model family, and the conversion command and recipe of record for each."
tags:
  - llm
  - radiance
  - models
  - reference
timestamp: 2026-10-30
---

# Radiance model families

The selection key is the exact **(architecture id, quantisation descriptor)** pair, so a family at
two weight formats is two `.so` files. A checkpoint's id is its `config.json` `model_type` without
underscores (`qwen3_5` → `qwen35`); `rad-convert --arch ID` overrides it. `data/recipes/` is the
authority: **read the recipe's header** — it names the exact `rad-convert` line, its `--set` keys
and whether it needs calibration.

## The plugin table

| plugin | id | quant | what it serves |
|---|---|---|---|
| `llama_fp8` | `llama` | `fp8_e4m3` | plain LLaMA decoder (MiniCPM5, Llama 3, derivatives reporting `model_type: llama`) from a checkpoint holding E4M3 codes + `weight_scale_inv` |
| `llama_dense_fp8` | `llama` | *(empty)* | the same graph from a bf16 checkpoint, linears made block fp8 by a recipe |
| `qwen35_bf16` | `qwen35` | *(empty)* | Qwen3.5/3.6/3.8 dense hybrid (GDN + gated attention), bf16 |
| `qwen35_fp8` | `qwen35` | `fp8_e4m3` | the same, block-scaled FP8 weights and activations |
| `qwen35_w8a8` | `qwen35` | `w8a8_fwht128` | int8 trunk: i8 weights, bf16 scale per 128 of K, 128-wide Hadamard, int8 activations |
| `qwen35moe_fp8` | `qwen35moe` | `fp8_e4m3` | `qwen35_fp8` with a routed feed-forward |
| `qwen4exp_fp8` | `qwen4exp` | *(empty)* | Qwen4-Exp / Qwen3.8-Flash-Next: a bf16 checkpoint quantised at convert, or Qwen's FP8 release as it ships |
| `glm5next` | `glm5next` | *(empty)* | GLM-5.3-Flash: four mHC residual streams, 34 KDA + 11 sparse MLA layers with a DSA indexer, 288 MXFP4 experts top-8, block-FP8 attention/dense at f32 scales, MTP drafter, vision tower |
| `hyv3_bf16` | `hyv3` | *(empty)* | Tencent Hy-Memory-30B-A3B bf16; bf16/W4/W8A8/block-FP8/MXFP4 by recipe |
| `hyv3_fp8` | `hyv3` | `fp8` | Hy-Memory-30B-A3B-FP8: imported per-tensor E4M3, one dense layer then sigmoid-routed MoE |
| `hyv3_gguf` | `hyv3` | `gguf_ftype_15` | a llama.cpp Hy-Memory Q4_K_M GGUF, dequantised and recipe-converted |
| `gemma4_bf16` | `gemma4` | `compressed-tensors` | Gemma 4 31B dense (and E2B/E4B at one rank): sliding-window + proportional-RoPE global attention, GELU, softcapped logits; int4/Q8 codes per 128; assistant (shared-KV), DFlash or DFlash2 drafter; vision |
| `gemma4` | `gemma4` | *(empty)* | Gemma 4 text from Google's bf16 checkpoint (26B-A4B MoE, dense sizes) with z-lab's DFlash |
| `gemma3` | `gemma3` | *(empty)* | Gemma 3 dense (TranslateGemma 27B): sliding-window + global attention, GemmaRMSNorm, GELU; bf16 or int8/MXFP4/asym-int4 linears; DFlash2 drafter |
| `lfm2_bf16` | `lfm2` | *(empty)* | LiquidAI LFM2 / LFM2-VL, bf16, one rank |
| `embgemma2` | `embeddinggemma2` | *(empty)* | EmbeddingGemma 2: bidirectional encoder with Gemma 4 vision tower and audio conformer, pooled |
| `nomicbert` | `nomicbert` | *(empty)* | nomic-embed-text-v2-moe: bidirectional post-norm encoder, 8 experts top-2 on every second layer, mean-pooled |
| `nemotron35_embed` | `mistral3` | *(empty)* | Nemotron 3.5 Embed 1B/8B and Rerank 8B: bf16 text/image retrieval with a Pixtral tower |
| `qwenimage21` | `qwenimage21` | *(empty)* | Qwen-Image 2.1 / 2.1-Turbo image generator and editor (diffusers pipeline) |
| `krea2` | `krea2` | *(empty)* | Krea 2 Raw/Turbo: Qwen3-VL-4B tapped layers, 12.9B single-stream DiT, Wan 2.1 VAE |
| `sdxl` | `sdxl` | *(empty)* | Stable Diffusion XL and finetunes (Illustrious, NoobAI, Pony), single-file checkpoint |
| `flux3` | `flux3` | *(empty)* | FLUX.3 [klein] and base: image generation and edits from up to ten pictures |
| `flux3distilled` | `flux3distilled` | *(empty)* | the same plugin under the step-distilled release's own pipeline name |
| `anima` | `anima` | *(empty)* | Anima Base/Aesthetic/Turbo from the release's three single files |
| `qwen3asr` | `qwen3asr` | *(empty)* | Qwen3-ASR: Whisper-style audio encoder over a dense Qwen3 decoder, speech to text |
| `minimaxmusic3` | `minimaxmusic3` | *(empty)* | MiniMax-Music3: Qwen3-8B frame model, depth decoder, flow-matching DiT, DAC vocoder |
| `breeze` | `breeze` | *(empty)* | Breeze-TTS-2: T5Gemma 2 text encoder, Qwen3 backbone, 16-codebook depth decoder, Qwen3-TTS 12 Hz codec |
| `fishomni` | `fishomni` | `bsgemm-moe` | Fish Audio drama-3: Qwen3.5-35B-A3B backbone, block-FP8 experts at f32 scales, 13-layer codebook tower, Fish S2 DAC/codec |
| `minimaxh3` | `minimaxh3` | *(empty)* | MiniMax-H3 video with stereo sound: Qwen3-VL-32B text encoder, 33B DiT, tiled ViT decoder, BigVGAN audio |
| `ltx2` | `ltx2` | *(empty)* | LTX-2.5 base/distilled: Gemma 4 LM + text connectors, duration head, audio-video DiT, causal video VAE, audio VAE |

## Recipes of record, by family

`$SRC` is a downloaded checkpoint; `$CALIB` is a calibration directory (see
[[Radiance Conversion]]). Paths are shortened to the recipe name.

| target | command |
|---|---|
| Qwen3.8-27B bf16 | `rad-convert $SRC -o q38-27b-bf16.rad --recipe data/recipes/q38-27b-bf16.recipe` |
| Qwen3.8-27B block fp8 + DFlash2 | `rad-convert $SRC -o q38-27b-fp8.rad --recipe data/recipes/q38-27b-fp8block-df2.recipe --draft-model $DFLASH2 --set quantization_config.quant_method=fp8 --set quantization_config.fmt=e4m3 --set "quantization_config.weight_block_size=128 128" --set quantization_config.activation_scheme=dynamic` |
| Qwen3.8-27B MXFP4 + DFlash2 | `rad-convert $SRC -o q38-27b-mxfp4.rad --recipe data/recipes/q38-27b-mxfp4-df2.recipe --draft-model $DFLASH2 --set quantization_config.quant_method=fp8 --set quantization_config.fmt=e4m3` |
| Qwen3.8-27B w4a16 (an int4 release) | `rad-convert $SRC -o q38-27b-w4a16.rad --recipe data/recipes/q38-27b-w4a16.recipe` |
| Qwen3.8-27B Quark AWQ-MXFP4 | `rad-convert $SRC -o q38-27b-quark.rad --recipe data/recipes/q38-27b-quark-mxfp4-df2.recipe --draft-model $DFLASH2` |
| Qwen3.8-27B ParoQuant int4/int5/MXFP4 | `rad-convert $SRC -o q38-27b-paro.rad --recipe data/recipes/q38-27b-paro-mxfp4-df2.recipe --draft-model $DFLASH2` |
| Qwen3.8-27B NVFP4 (compressed-tensors or ModelOpt) | `--recipe data/recipes/q38-27b-nvfp4-df2.recipe` or `q38-27b-modelopt-nvfp4.recipe`; every NVFP4 weight must take a rule (no kernel serves NVFP4) |
| Qwen3.8-Flash-Next bf16 reference | `rad-convert $SRC -o flashnext-bf16.rad --max-ctx 4096` (no recipe; served with `--weights-disk-tier`) |
| Qwen3.8-Flash-Next four-bit production | `CALIB=$CALIB rad-convert $SRC -o w4nl64-i8lm.rad --recipe data/recipes/qwen4exp-w4nl64-i8-hc8m.recipe` (GPTQ experts + int8 trunk) |
| Qwen3.8-Flash-Next uncalibrated four-bit | `--recipe data/recipes/qwen4exp-w4.recipe` (rtn, no calibration) |
| Flash-Next from an AutoRound int4 release | `--recipe data/recipes/qwen4exp-autoround-i8-hc8m.recipe` |
| Gemma 4 31B w4a8 (no calibration) | `--recipe data/recipes/gemma4-31b-dense-bf16-w4a8.recipe --set quantization_config.quant_method=compressed-tensors --draft-model $ASSISTANT` |
| Gemma 4 31B w4a8 + DFlash / DFlash2 | `gemma4-31b-dense-bf16-w4a8-df.recipe` / `-w4a8-df2.recipe`, same `--set` |
| Gemma 4 31B Q8 grid | `gemma4-31b-dense-bf16-q8-df.recipe` |
| Gemma 4 26B-A4B + DFlash | `gemma4-26b-a4b-df.recipe`; `-pad768` when the experts were padded to 768 (down may then be block fp8) |
| Gemma 4 E4B (Nemotron Bolt) | `gemma4-e4b-bf16-df.recipe`, `-i8g-`, `-a4-`, `-w4a8-`, `-w8a8-` variants |
| TranslateGemma 27B | `translategemma-27b-i8a8.recipe` (calibration container), then `CALIB=$CALIB translategemma-27b-mxfp4-gptq.recipe` (or `-df2`) |
| GLM-5.3-Flash | `rad-convert $AMD_QUARK -o glm53.rad --recipe data/recipes/glm53-mxfp4.recipe` |
| Hy-Memory-30B-A3B | `hy-memory-30b-a3b-bf16-fp8.recipe`, `-mxfp4`, `-w4`, `-w8`, `hy-memory-30b-a3b-fp8.recipe`, `hy-memory-30b-a3b-gguf-q4k-to-w4.recipe` |
| MiniCPM5-2B | `minicpm5-2b-dspark.recipe` (or `-bf16-dspark`) with `--draft-model $DSPARK` |
| Qwen3.6-35B-A3B | `q36-35b-a3b-fp8.recipe` |
| Qwen-Image 2.1 | `qwen-image-2.1-fp8.recipe` (Turbo uses the same file) or `-bf16` |
| Krea 2 | `krea-2-fp8.recipe`, `krea-2-bf16.recipe`, `krea-2-fp8-unscaled.recipe` for a plain-FP8 finetune file |
| FLUX.3 [klein] | `flux-3-klein-fp8.recipe` |
| SDXL / finetunes | `sdxl-bf16.recipe --tokenizer <openai/clip-vit-large-patch14>/tokenizer.json` |
| Anima | `anima-fp8.recipe` (or `-bf16`) + `--add` ×2 + `--config` + `--tokenizer2` + `--arch anima --set anima.variant=aesthetic` |
| LTX-2.5 | `ltx-2.5-fp8.recipe` (or `-bf16`); full DiT: symlink a folder whose `transformer/` is `transformer_full/` and `--set scheduler.use_dynamic_shifting=1 --set scheduler.shift_terminal=0.1` |
| MiniMax-H3 / FastH3 | `minimax-h3-fp8.recipe`, `minimax-h3-w8a8.recipe`, `minimax-h3-curve-*` for curve-form checkpoints |
| MiniMax-Music3 | `minimax-music3-bf16.recipe` |
| Breeze-TTS-2 | `breeze-tts2-bf16.recipe` |
| drama-3 | `drama3-fp8.recipe` |
| nomic-embed-v2-moe | `nomic-embed-v2-moe-bf16.recipe` |
| Unlimited-OCR | `unlimited-ocr-bf16.recipe` |
| Qwen3-ASR | no container: serve the checkpoint directory as it ships |
| EmbeddingGemma 2, Nemotron Embed/Rerank | serve the checkpoint, or convert bf16 with no recipe |

A checkpoint served at its own precision needs no container at all:
`radiance --model /srv/models/hf/Qwen/Qwen3.8-27B-FP8`. Convert when you want a tier only a container
has (quantised encodings, a drafter, a second vocab) or a smaller file.

## Family-specific traps

- **`head_dim` is read, never derived.** On the Qwen hybrids it is 256 while `hidden_size /
  num_attention_heads` is 213; a derived value silently breaks projection widths, KV page size and the
  attention kernel's band.
- **A fused projection shards by part, not by contiguous rows.** A tensor-parallel rank owns a slice
  of *each* stacked projection in a fused `[gate|up]` or `[q|k|v|z]`; a contiguous slice would hand
  rank 0 the whole gate, and the model would produce fluent wrong text. This is declared through
  `RadWeightDecl::row_parts`, never inferred from the container.
- **Gemma 4 26B-A4B:** the routed experts' `gate_up` may be block fp8, but `down` stays bf16 unless the
  experts were padded to 768 — hence the `-pad768` recipe.
- **GLM-5.3-Flash:** every weight is served as stored except the latent attention's small `kv_b`,
  decoded to bf16. Its KV cache is bf16 only (the plugin refuses `fp8` at startup), and at 172 GiB it
  needs `--tp 8`.
- **TranslateGemma 27B:** the checkpoint's template takes structured turns naming two languages and
  refuses the plain turn the server renders at startup. The container therefore serves a plain Gemma 3
  template, and a client sends on `/v1/completions` the prompt the checkpoint's own template renders.
- **ParoQuant containers made before 1.5.0 are refused at startup.** Convert again with the old
  container as `--reuse`; every tensor that did not change is copied.
- **SDXL carries no tokeniser.** Pass CLIP's `tokenizer.json` beside the single file. A Krea 2
  finetune shipped as one DiT file in Krea's key names is rewritten into a directory whose
  `transformer/` holds it (`scripts/krea2_native.py`), with the release's other parts copied in.
- **Anima** ships as three single files: `--add` the text encoder and VAE, `--config` a Qwen3-0.6B-Base
  directory (config + tokenizer), `--tokenizer2` ComfyUI's T5 tokenizer, `--arch anima`,
  `--set anima.variant=…`.
- **drama-3's codec is `codec.pth`**, a `torch.save` file read as data, never unpickled.
- **Generators that load LoRA files declare their module aliases**; the checkpoint and a ComfyUI port
  disagree in ways that load without error and generate garbage. The per-plugin alias table is in
  `docs/ARCHITECTURES.md` ("Adapter key names of the generators").
- **Licences travel with the checkpoint, not the engine.** Qwen-Image 2.1 is non-commercial;
  MiniMax-H3's licence excludes the EU, UK, Republic of Korea and USA; drama-3's community licence
  needs a commercial licence to serve speech to others, and cloning a real person needs consent;
  Breeze-TTS-2 is research/non-commercial.

## Related

- [[Radiance Conversion]] — the tool, recipe language and quantisers used above.
- [[Radiance Serve Options]] — the flags each family's compose file uses.
- [[Radiance Architecture Plugins]] — writing a plugin for a family not in this table.
- [[Quantization Production]] — the fleet's campaign and gates.