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Model Details
Model Provider
malaiwah
Model Tree
zai-org/GLM-5.3-Flash-BF16
Input Modalities
Output Modalities
Supported Functionality
The panel25 streaming-lane measurements: 25 windows, 51,175 scored positions, full-vocabulary KL(reference || candidate) in nats, with this artifact highlighted and its peers retained. K6 is plotted at 0.013714889 nats and K8 at 0.012384191 nats; these are the two-run streaming receipts, not K6's five-run sealed-ep8 result. Neither clean17 values nor cross-stack FP8 measurements are mixed into this plot.
This is inspection-only, not a certified ranking: the registry retains its scope, pipeline and missing-provenance limitations and draws no ranking line. The x-axis is recorded serialized bytes in GiB, not VRAM; K6/K8 use tensor-payload bytes while peers can use whole-repository bytes. The unquantized control has no recorded size, so it remains in the downloadable data with its exclusion reason rather than receiving an invented x-coordinate. No control subtraction is performed.
These are descriptive means on the historical panel: its 25 windows come from four source documents and include calibration-adjacent material. They do not establish population-level, native-serving or task-quality rankings; see the scope disclosures below.
Interactive highlighted plot · PNG · SVG · CSV and exclusions · Full provenance JSON · Live cached image
Registry snapshot: 598c441a2281963f1469ea4ec02d166081b3ac5a. The static plot and data are stored with this card; the live image is explicitly mutable. No model weights or measurement values were changed by this plot addition.
⚠ Scope disclosure — this number is a panel25 number
Added 2026-08-29. Nothing here is a correction: 0.012384 is and remains the correct mean over the full 25-window panel. What changed is that the panel is now known to contain calibration-adjacent windows, so the scope has to travel with the number.
brandonmusic ran a 13-gram overlap scan of his sealed panel against its own calibration-role windows and found that the whole
axis4_reasoningdomain shares 37–39 % of its 13-grams with calibration material — despite the panel being clean at the document-hash level. Document-hash dedup is not enough. He excluded that domain and scored his primary numbers on the 17 windows that survive. The finding, the scan and the 0.05 threshold are his.Every malaiwah number on this panel used all 25 windows, so every one of them carries the same contamination. Recomputed on his clean scope, from our own published per-window arrays (no GPU, no re-measurement — this is arithmetic on data already published):
Table with columns: panel25 (published), clean17 (his scope), move panel25 (published) clean17 (his scope) move
Mean KLD(teacher ‖ K8) = 0.012384191023436866 over the full sealed panel
(25 windows / 51,175 positions), with matching recorded tokenwise-KL digests
and means in two cold runs (bitwise_deterministic: true in the receipt).
This is conditional repeatability, not universal determinism or independent
textual replication. The receipt's quality gate passed.
Receipt: receipts/stream-k8-kld.json.
These raw values are a mixed-design inventory, not a ranking. Equal panel identity is necessary; the actual pair predicate must also pass.
| Model | Mean KLD (nats) | Size | Lane |
|---|---|---|---|
| This K8 | 0.012384 | 331 GB | streaming, 2 runs |
| K6 | 0.013715 | 254 GB | streaming, 2 runs |
| K6 (sealed 8×H200, 5 runs) | 0.013723 | 254 GB | sealed EP8 |
| Official FP8 | 0.020615 |
Historical single-window diagnostic, not comparable to the panel means:
| Model | Mean KLD (nats) | Size | Lane |
|---|---|---|---|
| NVFP4 | 0.060535 | ~180 GB | his stack, 1 window |
Correction, 2026-09-07. The "1.66× closer" FP8 headline is withdrawn: its runtime differs. K8 is 331 GB versus FP8's 328 GB and K6's 254 GB. Separately, the sampled weight-space experiment found 13.2× lower NMSE for K8 (3.505e-5 vs 4.624e-4, 30/30 sampled matrices with the permutation undone). Weight-space NMSE is not a serving-quality or whole-model proof.
Lane disclosure. Measured on the single-GPU streaming lane (~$6/model),
not the 8×H200 sealed lane. The lanes were bridged on this exact panel: K6
reads 0.013714889 streaming vs 0.013723385 sealed — −8.5e-6 (0.06 %), with
the worst single window differing by 2.9e-4. The streaming receipt sets
publishable_as_reproduction: false because a different expert-combine order
is an independent measurement that agrees closely, not a bitwise reproduction.
The checkpoint measurement reconstructs weights through the reference forward; it does not measure native-serving activation/cache/kernel numerics, or prove native decode/forward equivalence. Weights-only KL is not a lower bound on served KL: omitted perturbations may amplify or cancel divergence. The serving qualification below concerns its pinned deployment, not equivalence to this fidelity measurement or a current remote-status check.
Single-window limitation. On this panel, per-window KLD sd is 7.2e-3
(K6) / 6.9e-3 (K8), and paired K6−K8 sd is 2.0e-3 versus mean 1.33e-3.
The direction reversed on window-0000. A one-window result describes that
window, not a full-panel or population rate comparison; the full-panel
ordering is descriptive, not "decisive" independent-document inference.
Historical investigation.
(Called "quantization-attributable error" before 2026-08-31; renamed per peer-review P1-05 — the difference estimates excess divergence over the same-lane unquantized control and is not a causal attribution.)
Scoring the unquantized BF16 weights against this teacher on this panel already costs 0.011506 nats — the price of the comparison itself (teacher captured on a different runtime; bf16 addition is not associative across differing expert-combine orders). Two cold runs, identical means. Subtracting it:
| panel KLD | excess over control | |
|---|---|---|
| BF16 (floor) | 0.011506 | — |
| K8 (331 GB) | 0.012384 | 0.000878 |
| K6 (254 GB) | 0.013715 | 0.002209 |
K8's residual is smaller than K6's — 0.000878 vs 0.002209 nats — where the raw means sit only 1.11x apart, because the floor is common to both rows and dominates both. The previously published ratio of the two residuals ("2.52x") is withdrawn: a ratio of small residuals magnifies control error and carried no uncertainty. Read the residuals beside the raw values, with the floor named. Method, receipts and the ways this subtraction can be misused: BF16-FLOOR.md.
c5d9c657),
through brandonmusic's GLM-5.3 pipeline
with a disclosed patch series. His published core admits K3/K4/K5, so K8 is
a declared rate extension — our encoder was verified byte-identical to
his sealed core across 120 encodes / 624 MiB / 0 differing bytes
(evidence,
issue #1).
This establishes sampled codec equivalence, not every historical campaign
matrix or native decode/forward equivalence.malaiwah/glm52-exl3-vast
with MODEL_PROFILE=glm53-k8. The image pins the qualified Glm5Next vLLM,
B12X sparse-attention stack, native EXL3 K8 extension, CUDA, and fail-closed
runtime overlays as one contract.Pins: BF16 source zai-org/GLM-5.3-Flash-BF16 (weights == a6c167b6);
calibration = brandonmusic's published EP4 captures (sealed inventory
f56e9d62… adopted verbatim). Deviations, all receipted: encoded on 4×H200
SM90 (his campaign attests 4×B200 SM100; fat 9.0;10.0 extension build), K4-KL
gate satisfied via a disclosed bridge document carrying his real published K4
receipt hashes, measurement on the streaming lane at EP8 emulation with fp32
combine order. Materialization receipt: bits 8, complete,
main_and_mtp_complete, nonrouted_native_exact, 331,449,761,784 logical
bytes, 37,152 routed choices, 1,618 native tensors.
Z.ai published two sibling roots for this model and neither declares the other:
zai-org/GLM-5.3-Flash (the
FP8 release, where most traffic lands) and
zai-org/GLM-5.3-Flash-BF16
(the BF16 weights). This quant declares BF16 as its base_model because
that is what it was actually quantized from — the FP8 release is a sibling
quantization of the same model, not our source. The fidelity reference here is
the pinned BF16 teacher; FP8 is a separately measured cross-stack candidate,
not the reference. A declared base-model link alone does not prove another
publisher's weight provenance.
Related work on the same model, all measured on one panel in the quant-fidelity registry: brandonmusic 4bpw, 0xSero Dione Q4, orcarouter MLX. Collection: GLM-5.3-Flash — measured quants & fidelity.
Base model by Z.ai. Quantization pipeline, calibration captures, and teacher panel by brandonmusic — co-credited, see the collaboration thread. Trellis codec and kernels by turboderp. Every tool, patch, receipt and the full campaign log: malaiwah/quant-fidelity-suite. Receipt-backed measurements with per-group comparability limits: quant-fidelity-registry.
The shipped profile is glm53-k8. It was booted on 4× RTX PRO 6000
Blackwell 96 GiB and passed arithmetic, factual, instruction-following, strict
structured-output, and tokenizer-exact 32K retrieval startup gates. The final
published image was then pulled by digest and smoke-tested without source or
runtime-overlay mounts.
a0d05f76994cf44f3667c0d2910d3b0e4d305d23b5ef443adce36ba5a10f2d5aa682fc9f2f0d0faeverdictai/glm53-flash-exl3-k4@sha256:0f1cdcc8891f1cc3a444121eb61d366289a1cbba285f0892dcbb24bc94961692ghcr.io/malaiwah/glm52-exl3-vast@sha256:5a0d4b370e9f6a2ef85fa8b8c213492122554b34ba18d630a3a78130758914cfThe eight overlapping 16-bit MCG windows for K8 span 72 bits, while B12X's
fused EXL3 decoder represents that state in two 64-bit words. The runtime
therefore fails closed instead of merely widening the fused decoder's bitrate
guard. This profile uses ExLlamaV3's compiled native K8 extension and passes the
actual uniform layer bitrate into the K8 dispatch. VLLM_EXL3_PREFILL_CAPACITY
is bounded to the scheduler's 512-token batch and eager mode avoids an
unqualified graph path. B12X sparse MLA and the rest of the qualified GLM-5.3
stack remain enabled.
The engine exposed 6,610,733 logical KV tokens, or 14.41 maximum-length requests. Per-GPU profiling reported 78.94–78.97 GiB weights plus non-torch, 2.25 GiB peak activations, zero graph memory, and 7.10–7.14 GiB KV.
Two independent 448K trials each built a tokenizer-exact 449,461-token document and retrieved all three facts, in 170.775 and 175.086 seconds. Short and strict structured-output checks still passed after the long-context stress. The common 458,752-token K6/K8 cap is a correctness boundary, not an extrapolation from KV capacity.
Unique-prefix prefill, one request, no prefix reuse:
| prompt | tok/s |
|---|---|
| 8K | 2,684 |
| 32K | 2,825 |
| 64K | 2,938 |
| 128K | 2,986 |
Aggregate target-only decode (MTP_TOKENS=0), eight requests per level:
| input context | C1 tok/s | C4 tok/s | C8 tok/s |
|---|---|---|---|
| 256 | 10.29 | 38.79 | 75.66 |
| 32K | 8.42 | 23.43 | 28.46 |
| 128K | 5.42 | 12.05 | 13.25 |
All 72 requests completed without failure, preemption, or prefix reuse. These are measurements from one four-GPU PCIe host, not guarantees for other topology, clock, thermal, driver, storage, or request mixes.
On panel25's streaming lane, K6 records 0.013715 and K8 0.012384 nats; K6's sealed-ep8 value is separately 0.013723. Subtracting only the streaming BF16 control gives descriptive excesses of 0.002209 and 0.000878 nats, respectively, not causal quantization error or a native-serving advantage. The cost is about 77 GB / 30% more checkpoint bytes, about 15.2 GiB more non-KV memory per GPU, and about 14.4 GiB less KV per GPU. On the recorded deployment matrices, K6 is 5.3–7.3× faster at short context and 8.3–24.4× faster when the measured 32K/128K prefill cost is included. K6 remains the appliance's production default. Lower checkpoint KL does not establish closer native-serving output.
Prerequisites: Linux x86-64, four visible RTX PRO 6000 Blackwell GPUs, NVIDIA driver ≥ 590.48.01 / CUDA 13.2 compatibility, the NVIDIA Container Toolkit, and roughly 400 GiB free persistent storage for the checkpoint plus caches. PCIe P2P on this card family requires NVIDIA's open kernel modules; see the RTX 6000 Pro multi-GPU notes.
yaml
name: glm53-k8services: api: image: ghcr.io/malaiwah/glm52-exl3-vast@sha256:5a0d4b370e9f6a2ef85fa8b8c213492122554b34ba18d630a3a78130758914cf pull_policy: always restart: unless-stopped network_mode: host ipc: host shm_size: 32gb stop_grace_period: 2m ulimits: memlock: soft: -1 hard: -1 environment: MODEL_PROFILE: glm53-k8 AUTH: key VLLM_API_KEY: ${VLLM_API_KEY:?set VLLM_API_KEY to a long random secret} HF_TOKEN: ${HF_TOKEN:-} SSH_ENABLED: "0" SOUL_ENABLED: "0" VERIFY_HEALTH_TIMEOUT_S: "3600" volumes: - /srv/glm53-turnkey:/workspace - /srv/glm53-cache:/cache deploy: resources: reservations: devices: - driver: nvidia count: 4 capabilities: [gpu]bash
sudo mkdir -p /srv/glm53-turnkey /srv/glm53-cacheexport VLLM_API_KEY="$(openssl rand -hex 32)"docker compose up -ddocker compose logs -fFirst boot downloads about 309 GiB and can take substantial time. The container is ready only after the log reports
text
>>> Verified: serving; long-context retrieval verifiedhttp://HOST:8000/v1; dashboard:
http://HOST:1111. The served model name is GLM-5.3-Flash-K8.
bash
curl http://127.0.0.1:8000/v1/chat/completions \ -H "Authorization: Bearer $VLLM_API_KEY" \ -H "Content-Type: application/json" \ -d '{"model":"GLM-5.3-Flash-K8","messages":[{"role":"user","content":"Reply with exactly READY"}],"max_tokens":256}'Do not replace only the checkpoint path in another vLLM command. The profile, parent digest, runtime overlays, quantization, attention backend, DCP topology, KV calibration, scheduler, and eager execution mode are one qualified contract.
>>> Verified: serving; long-context retrieval verifiedname: glm53-k8services: api: image: ghcr.io/malaiwah/glm52-exl3-vast@sha256:5a0d4b370e9f6a2ef85fa8b8c213492122554b34ba18d630a3a78130758914cf pull_policy: always restart: unless-stopped network_mode: host ipc: host shm_size: 32gb stop_grace_period: 2m ulimits: memlock: soft: -1 hard: -1 environment: MODEL_PROFILE: glm53-k8 AUTH: key VLLM_API_KEY: ${VLLM_API_KEY:?set VLLM_API_KEY to a long random secret} HF_TOKEN: ${HF_TOKEN:-} SSH_ENABLED: "0" SOUL_ENABLED: "0" VERIFY_HEALTH_TIMEOUT_S: "3600" volumes: - /srv/glm53-turnkey:/workspace - /srv/glm53-cache:/cache deploy: resources: reservations: devices: - driver: nvidia count: 4 capabilities: [gpu]sudo mkdir -p /srv/glm53-turnkey /srv/glm53-cacheexport VLLM_API_KEY="$(openssl rand -hex 32)"docker compose up -ddocker compose logs -fcurl http://127.0.0.1:8000/v1/chat/completions \ -H "Authorization: Bearer $VLLM_API_KEY" \ -H "Content-Type: application/json" \ -d '{"model":"GLM-5.3-Flash-K8","messages":[{"role":"user","content":"Reply with exactly READY"}],"max_tokens":256}'| 0.012384 |
| 0.010829 |
| −12.55 % |
| K6 sealed | 0.013723 | 0.011677 | −14.91 % |
| K6 streaming | 0.013715 | 0.011676 | −14.87 % |
| official FP8 | 0.020615 | 0.018665 | −9.46 % |
| BF16 floor (cross-stack) | 0.012712 | 0.010648 | −16.24 % |
| brandonmusic 4bpw | 0.024555 | 0.024949 | +1.61 % |
Correction, 2026-09-07. The former 1.66×/1.72× FP8 quality ratios are withdrawn: those rows change runtime/lane as well as weights. The sealed-K6/streaming-K8 BCa contrast also mixes lanes. Same-lane K6stream−K8 means are 0.001331 (panel25) and 0.000847 (clean17), descriptive of the fixed panel, not general quantizer quality.
Statistical correction (2026-08-31, peer review P1-15). This panel's 25 windows derive from only four source documents (clean17: three), so window-level sign tests and intervals describe these exact windows rather than independent evidence. The historical document-level calculation reported all four (three) document means favouring K8 and exact sign-test p = 0.125 (panel25) / 0.25 (clean17). It too compared sealed K6 with streaming K8; these p-values are not evidence of a same-lane or population quantizer advantage. The window-level p = 0.0041 / 0.049 are withdrawn as inferential statements. Use the same-lane descriptive means above, without extrapolating beyond this panel.
Do not difference a panel25 number against a clean17 one. They are answers
to different questions. Our registry enforces this structurally: clean17 is
its own derived panel with its own comparability key.
The excess-over-control table below (formerly "quantization-attributable"; renamed 2026-08-31, P1-05) cannot be recomputed on the clean scope — its floor is the streaming BF16 floor, whose receipt is scalar-only (run means and a tokenwise digest, no per-window array), and substituting the cross-stack floor would be the cross-lane subtraction our registry refuses. It stands as a panel25 number.
Full recompute, with per-domain tables, paired intervals and provenance:
reports/clean-scope-recompute.json.
Working: PROTOCOL-ALIGNMENT.md §4.
Padding correction, 2026-09-07. The teacher's ~1.6e-8 padded mass is
measured on real final-0000 logits; the ~1e-10 masking effect is from
synthetic students, not this quant's full-panel logits. Sharing head
weights does not imply equal hidden states or padded probability mass.
The former KLD × mass equality and ninth-digit "masked equivalent"
claim are withdrawn. Actual masked full-panel values remain unmeasured;
published unmasked metrics and historical study receipts are unchanged.
Study and correction.
| 328 GB |
| cross-stack |
| brandonmusic 4bpw | 0.024555 | 176 GB | his stack |
| 0xSero Dione Q4 | 0.027263 | 188 GB | our measurement |
glm5_nextdown_proj, K6 on gate/up) is offline CPU assembly, no GPU
re-encode. The parts bin is published: GLM-5.3-Flash-TR3-partsbin-v1.
Assembly does not reproduce a fresh encode with down-projection Hessians
conditioned on the mixed gate/up choice; the mixed artifact needs its own
fidelity measurement.