Mortdecai
6bce2d4c3b
google/diffusiongemma-26B-A4B-it (released 2026-06-10) — Google's first open-weight text-diffusion LLM. Does NOT run in Ollama (unknown arch 'diffusion-gemma'); built llama-diffusion-cli from ggml-org/llama.cpp PR #24423 and smoke-tested Q4_K_M on steel141's 3090 Ti. - New reference doc with specs, build recipe, throughput, and gotchas - CORPUS_ollama_variants.md: "not an Ollama variant" callout - README index line for the reference doc - scripts/diffusiongemma-smoketest/ harness + raw result logs Findings: ~106 tok/s effective / ~2030 tok/s in-step-parallel; correct code + coherent reasoning; <|channel>thought CoT eats the 256-tok canvas so strict short formats need block budgeting. nvidia-smi index != CUDA index on steel141 (select 3090 Ti by UUID). Experimental research artifact, not homelab-deployable until diffusion arch merges to llama.cpp mainline. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
32 lines
4.4 KiB
Plaintext
32 lines
4.4 KiB
Plaintext
0.00.841.557 W load: control-looking token: 212 '</s>' was not control-type; this is probably a bug in the model. its type will be overridden
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0.00.842.233 W load: control-looking token: 50 '<|tool_response>' was not control-type; this is probably a bug in the model. its type will be overridden
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0.00.879.927 W load: special_eog_ids contains '<|tool_response>', removing '</s>' token from EOG list
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0.04.814.391 I diffusion: -n 48 -> 1 blocks, n_ubatch=2304 n_batch=2304 n_ctx=2304 (canvas_length=256)
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0.04.814.394 I diffusion: --fit has no effect here; context is sized from -n and the canvas. Set -ngl / --n-cpu-moe to control device memory.
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0.04.814.907 W llama_context: n_ctx_seq (2304) < n_ctx_train (262144) -- the full capacity of the model will not be utilized
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0.04.819.412 W sched_reserve: layer 5 is assigned to device CUDA0 but the Flash Attention tensor is assigned to device CPU (usually due to missing support)
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0.04.819.415 W sched_reserve: Flash Attention was auto, set to disabled
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0.07.106.365 I diffusion_params: steps=128 schedule=0 algorithm=4 temperature=0.800 eps=0.001000 mask_token=4
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0.07.106.635 I diffusion_eb: max_steps=48 t=[0.400,0.800] entropy_bound=0.1000 stability=1 confidence=0.0050 kv_cache=on gpu_sampling=on sample_reduce=on
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0.07.107.839 W init: embeddings required but some input tokens were not marked as outputs -> overriding
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0.07.565.506 I
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diffusion step: 0/48 [ ] 0%0.07.667.965 I
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diffusion step: 1/48 [= ] 2%0.07.772.514 I
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diffusion step: 2/48 [== ] 4%0.07.876.431 I
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diffusion step: 3/48 [=== ] 6%0.07.981.552 I
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diffusion step: 4/48 [==== ] 8%0.08.087.446 I
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diffusion step: 5/48 [===== ] 10%0.08.196.277 I
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diffusion step: 6/48 [====== ] 12%0.08.302.551 I
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diffusion step: 7/48 [======= ] 14%0.08.407.803 I
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diffusion step: 8/48 [======== ] 16%0.08.514.697 I
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diffusion step: 9/48 [========= ] 18%0.08.621.268 I
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diffusion step: 10/48 [========== ] 20%0.08.728.440 I
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diffusion step: 11/48 [=========== ] 22%0.08.835.336 I
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diffusion step: 12/48 [============ ] 25%0.08.942.227 I
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diffusion step: 13/48 [============= ] 27%0.09.050.835 I
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diffusion step: 14/48 [============== ] 29%0.09.160.522 I
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diffusion step: 15/48 [=============== ] 31%0.09.268.593 I
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diffusion step: 16/48 [================ ] 33%0.09.377.200 I
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diffusion step: 17/48 [================= ] 35%0.09.485.784 I
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diffusion step: 18/48 [================== ] 37%0.09.595.474 I
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diffusion step: 19/48 [=================== ] 39%0.09.704.166 I
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diffusion step: 20/48 [==================== ] 41%
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<|channel>thought
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* Topic: Primary colors of light.
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* Constraint 1: Exactly five colors.
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* Constraint 2: One per line.
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* Constraint 3: Nothing else (no intro, no outro).
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* The standard primary colors of light (additive) are Red, Green, and Blue (3 colors).
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* Wait, the user is asking for *exactly five*.
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* Is there a system with five primary colors of light?
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* Standard RGB = Red, Green, Blue (3).
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* CMY (subtractive) = Cyan, Magenta, Yellow (3).
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* RYB (artistic) = Red, Yellow, Blue (3).
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* Some color space models or specific display technologies might use more primaries.
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* However, strictly speaking, "primary colors of light" refers to RGB.
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* If I must list *five*, I might need to look at a specific model or include the primaries and sub-primary/secondary colors, or perhaps the user is testing the model.
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* Actually, usually, when a prompt asks for "exactly X" of
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total time: 2596.66ms, time per step: 123.65ms (21 steps over 1 blocks, entropy-bound)
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throughput: 98.6 tok/s (256 tok in 2596.66ms), in-step parallel 2070 tok/s (256-tok canvas x 21.0 steps/block)
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WALL_SECONDS=10.416765713 RC=0
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