Frank
219a097b39
Every payload swap a live endpoint has ever run is now one row in that endpoint's Eras table, with its rollback path in the same row. No per-attempt page, no per-swap ledger, nowhere else. - Added: LLM/frank-archon.md (radiance, 2x R9700 TP=2), LLM/frank-dragoon.md (halogen flash-server, 19 eras), LLM/frank-zealot.md (llama.cpp PrismML fork on the 3090). Each carries Current shape, Eras, Laws, wire contract, files. - Deleted: 45 per-payload runbooks -- the frank-dragoon line (11 including the pre-name halogen/kingjones/kairic/CIRU/eemin/agentionai/dflash2 pages and the benchmark page), the frank-zealot line (llama.cpp/vLLM/ik_llama/SGLang eras), the frank-archon line (vLLM/FreeToken/R9V/llama.cpp/radiance eras), plus frank-medium, frank-npu and the ubatch/PCIe one-offs that owned nothing. - Rewired: every wikilink and markdown-path reference to a folded page points at the endpoint page instead; the three Research see-also lists and the ubatch sweep's runbook link included. No anchored links existed in the set. - Regenerated both index pages as pure locators -- one row, one clause, no numbers -- so the docs_completeness locator law holds for all 153 pages. tests/docs_completeness.bats green: index links every page, no unresolved links. The pages moved to .AGENTTRASH/20261018-doc-dedupe/LLM/ (gitignored, and git history holds every byte).
124 lines
6.0 KiB
Markdown
124 lines
6.0 KiB
Markdown
---
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type: reference
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title: GGUF Compatibility and Runtime Lock-in
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description: How to answer "will engine X load this GGUF?" from the file's header alone, why a custom tensor type forces the runtime, and the discipline for pinning a fork build that can actually serve the file.
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tags: [gguf, llama.cpp, forks, quantization, speculative]
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timestamp: 2026-10-05T00:00:00-07:00
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---
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# GGUF Compatibility and Runtime Lock-in
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**The law: a GGUF's tensor-type histogram and ftype pick the runtime — read the
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header before promising a file to any loader.** Stock llama.cpp, Ollama and LM
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Studio refuse custom types at load (`unknown tensor type`); a fork-private type
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means exactly one engine can serve the file. Measured on this fleet repeatedly:
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`Qwen3.8-27B-Q8_0_ROCMFPX_AGENT.gguf` is ftype 115 with 311 tensors of type 103
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(`GGML_TYPE_Q8_0_ROCMFPX`) — only charlie12345/ROCmFPX reads it. The full type
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tables live in [[Llama Cpp Runtimes]] and [[Llama Cpp Code Diff]]
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(ggml_type 100–108, ftype families 100–106 / 110–113 / 118).
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## 1. Read the header, do not guess
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Parse the GGUF KV section and histogram the tensor types plus
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`general.architecture.file_type` — one python read over the first few MiB, no
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model load. Counting types out of the KV section settles a runtime argument in
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minutes; repo names and model cards do not.
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## 2. Compare routing variants by tensor mix, not by name
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Two files of the same quant can differ in how many tensors stay at plain Q8_0
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(measured: 187 vs 2 output-head tensors in an `_AGENT` variant of the same
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size). That difference is what moves spec-decode acceptance (0.953 vs 0.911)
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— the "same size" file is not the same file.
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## 3. Pin the build by commit SHA
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A fork that can read the file today can still crash mid-load: the 2026-08-25
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ROCmFPX builds read the ftype-115 file and then SIGSEGV in
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`ggml_compute_forward_set_rows`. Record the SHA in the build script
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(`scripts/build-rocmfpx.sh` pins `36e9acd`) and check it out explicitly — never
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a branch.
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## 4. Header diff method (candidate vs known-good)
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Answer "will engine X load this GGUF?" by diffing the candidate's header
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against a file the engine **already loads** — never by filenames or model cards;
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filenames lie about quantization and about MTP/vision heads.
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1. **Get the bytes**: both files, from byte 0, at least 64 MiB. Tokenizer KVs
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(151k token strings + merges) routinely eat 5–8 MiB, so a small range
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desynchronises the parser. True size from `curl -sIL` → `x-linked-size`
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(a bare HEAD `Content-Length` can lie):
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```sh
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curl -sL -r 0-67108863 -o cand.bin \
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"https://huggingface.co/<owner>/<repo>/resolve/main/<file>.gguf"
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ssh <host> 'head -c 67108864 /path/to/known-good.gguf' > good.bin
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```
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2. **Parse — and lock the parser against the known-good file first.** Layout
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(v2/v3): `magic[4]` `version u32` `n_tensors u64` `n_kv u64`, then KVs, then
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tensor infos. Strings are u64 length + bytes. **The value-type enum is NOT
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llama.cpp's `gguf.h`:** in the files seen (2026-09-28, unsloth + ajgazin UD
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GGUFs) type **8 = STRING, 9 = ARRAY**; llama.cpp's header has STRING=2,
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ARRAY=3 and desynchronises immediately. Working table:
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```
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0 u8 1 i8 2 u16 3 i16 4 u32 5 i32 6 f32
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7 bool 8 STR 9 ARRAY(u32 et, u64 n) 10 u64 11 i64 12 f64
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```
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Validate before trusting: the parse is right iff the tensor-info block ends
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somewhere sane and names look real (`blk.0.attn_q.weight`,
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`token_embd.weight`, `output_norm.weight`). EOF throw = wrong enum or
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offset — do not work around it.
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3. **Diff what engines actually bind on**: `general.architecture`; tensor
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count; tensor name list in order; per-tensor `ggml_type` and dims; geometry
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KVs (`<arch>.block_count`, `.embedding_length`, `.feed_forward_length`,
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`.attention.head_count[_kv]`, `.rope.*`, `.ssm.*`, `.context_length`,
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`.nextn_predict_layers`); MTP tensors (`nextn` in the name); vision tensors
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(`visual`, `v_` prefixes). A same-family fine-tune quantized by the same
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tool usually comes out byte-identical in every one of these — that is the
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answer.
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4. **Then read the engine's source before calling a delta a blocker.** A
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metadata difference only matters if the engine reads that key
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(`grep -rn "file_type\|recurrent_layers\|full_attention_interval" <src>/`).
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Worked example (gufo v0.1.1): `general.file_type` is deliberately not
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consulted (UD-*_K_XL ships a stale ftype 15; the tensor table rules), and
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`qwen35.attention.recurrent_layers` is never read (layer kinds come from
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`full_attention_interval`) — both deltas were non-issues the header diff
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alone would have flagged wrongly.
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5. **Say what you did not do.** Header analysis is strong evidence, not a
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load. State byte sizes, check free disk before proposing a fetch, and do
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not download tens of GB unasked — pointing the engine at the file is the
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definitive test.
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**Report shape:** verdict first (loads / will not / loads-with-caveats), then
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the side-by-side diff table, then only the load-bearing caveats: text-only vs
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vision tensors, chat-template differences (matters for llama.cpp, not for
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engines with compiled-in Jinja), license, disk headroom, and whether the base
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model is abliterated/uncensored.
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## 5. A/B a fork's spec decode by stripping the whole flag set
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`--model-draft` without `--spec-type` segfaults at load (measured 2026-10-02,
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core dump, no diagnostic). A baseline "no-draft" arm must remove `--model-draft`
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AND every `--spec-draft-*` AND `--spec-type` together — the flags move as a set.
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## 6. Before deleting a retired payload, read the rollback tag's env file
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A rollback may need a small companion dir: a drafter living in a directory
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named after an old quant looks like trash but is load-bearing. Same class as
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the gufo payload removal of 2026-10-03, which turned that rollback into a
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re-download.
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## Related
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- [[Llama Cpp Runtimes]] — which fork ships which custom types
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- [[Llama Cpp Code Diff]] — the enum tables and code-level differences
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- [[frank-dragoon]] — the ftype-115 lock-in in production
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- [[Llama Cpp Serving Sizing]] — pricing what a payload costs once it loads
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