ggml-org/llama.cpp b10448

on GitHub

model: add Kimi-K3 text model (#26185)

• model: add Kimi-K3 text model

Hybrid KDA (linear) + MLA (full) attention as in Kimi-Linear-48B, plus five
things that architecture does not have:

1. cross-layer residual attention (attn_res_block_size)
2. latent MoE (routed experts run at n_expert_latent)
3. situ activation (replaces SwiGLU everywhere)
4. MLA output gate (sigmoid gate before o_proj)
5. full-rank KDA gate (single ssm_g instead of ssm_g_a/ssm_g_b)

K3's text_config reports KimiLinearForCausalLM - the older 48B architecture -
so get_model_architecture routes on the top-level name instead.

The KDA decay gate has two forms, selected by linear_attn_config's
gate_lower_bound. It is not a clamp: when set it swaps the activation entirely
(fla/ops/kda/gate.py), from -exp(A_log)softplus(x) to
lower_boundsigmoid(exp(A_log)*x). K3 sets it to -5.0; kimi-linear leaves it
unset, so that path is unchanged.

Cross-layer residuals reuse ggml_dsv4_hc_pre for the weighted sum. That op is
CPU + CUDA only, so Metal/Vulkan will fall back per-node until those kernels
exist.

The routed experts ship as compressed-tensors "mxfp4-pack-quantized". That is
bit-compatible with ggml's MXFP4 - same E2M1 code assignment, same E8M0 scale
byte, only the nibble positions within a block differ - so they are repacked
rather than dequantized, losslessly and without a ~5.5 TB bf16 round-trip.
The repack is built lazily because gguf_writer holds every added tensor until
the final write. DeepSeek-V4 was already doing the identical bit-shuffling, so
it now shares the helper.

Verified against Moonshot's own code path (transformers + fla's Triton KDA
kernels) on a tiny model exercising every K3-specific feature. Final-position
logits vs the fp32 reference: 6.7e-05 rel / corr 1.00000000 for both the
chunked and the recurrent delta-net path. MXFP4 blocks dequantize to the source
weights with 0.0e+00 error.

Assisted-By: Claude Opus 5 (1M context) noreply@anthropic.com

• model: fix ty errors in the Kimi-K3 converter

• _res_parts buffers (kind, tensor) pairs, not bare tensors
• get_tensors must return an Iterator, matching ModelBase
• LazyBase's func takes one argument, so pass the expert loaders through
  args instead of the closure
• borrowing KimiLinearModel.set_vocab from an unrelated TextModel is
  deliberate and safe, but not expressible in the signature

No behaviour change: the MXFP4 repack still dequantizes to the source weights
with 0.0e+00 error and end-to-end logits are unchanged (8.386e-03 rel,
corr 0.99996630).

Assisted-By: Claude Opus 5 (1M context) noreply@anthropic.com

• Update conversion/kimi_k3.py

Co-authored-by: Boris Dvorkin b_dvorkin@niuitmo.ru

• Increase LLAMA_MAX_EXPERTS from 512 to 1024

• tests : support for Kimi K3 in archs test

• chat : add Kimi K3 chat format (reasoning, content, typed tool calls)

K3's assistant output is an XTML-ish tagged format built by the template's
open_tag/close_tag macros. Two properties break generic parsing:

1. The generation prompt ends with open_tag('think'), so the completion
   starts inside the think section with no opening marker in the output
   (thinking_forced_open).
2. Only <|open|>/<|close|>/<|sep|>/<|end_of_msg|> are special tokens; tag
   names ("think", "response", "message") are ordinary text tokens.

Adds common_chat_params_init_kimi_k3 (PEG_NATIVE) with detection on the
marker trio, reasoning extraction, response unwrapping, and tool-call
parsing of the tools/call/argument tag structure with argument types
taken from the tool schema. Includes the K3 chat template fixture and 9
test-chat cases derived from real generations of the full 2.8T model.

Verified end-to-end against Kimi-K3-Q2_K (GrEarl/Kimi-K3-GGUF) on 8x B200:
content, reasoning_content, streaming deltas, and tool_calls all correct;
finish_reason stop/tool_calls as appropriate.

Co-Authored-By: Claude Fable 5 noreply@anthropic.com

• chat : add message_delimiters for Kimi K3

Per-role message-start markers for token-level span splitting. User and
assistant messages carry only the role attribute, so their full opener
(through <|sep|>) is used; system and tool messages continue with more
attributes (type=/tool=/index=), so those delimiters stop after the
role's closing quote. Verified against the K3 tiktoken vocabulary that
the closing quote is always a standalone token across all attribute
variants, so the token-level prefix match stays exact.

Co-Authored-By: Claude Fable 5 noreply@anthropic.com

• fix: apply nits from @ngxson and text fixes from @danielhanchen

• tests : added missing hyperparameters and tensors for Kimi K3 in test-llama-archs

• chore : move overly verbose header file comments to Kimi K3 source file

• tests : re-enabled KIMI_K3 in test-llama-archs for WebGPU backend

• model-saver : emit kda_gate_lower_bound for Kimi K3

Quick fix. The Kimi K3 loader reads kda_gate_lower_bound and gates a graph branch on it (it scales the KDA gate when the bound is above -INFINITY), but the model
saver never wrote the key, so a save->load roundtrip silently dropped it back to the -INFINITY default and changed the model's output. The real K3 config sets gate_lower_bound = -5.0.

I propose to emit it from the saver, and set it to -5.0 in the test-llama-archs K3 case so the roundtrip check exercises it (the roundtrip fails without the saver line).

• Refactor conditional for model architecture check

• tests : re-enabled (again) KIMI_K3 and MINIMAX_M3 in test-llama-archs for WebGPU backend

• fix code comments

• add template on conversion

• move repack_mxfp4_blocks to model base

• nits

• add_value_length

• optimize res_stack construction

• nits

Co-authored-by: Boris Dvorkin b_dvorkin@niuitmo.ru
Co-authored-by: Stanisław Szymczyk sszymczy@gmail.com
Co-authored-by: Deepankar Singh singh.deepankar39@gmail.com
Co-authored-by: Claude Fable 5 noreply@anthropic.com
Co-authored-by: Caleb DeLeeuw caleb.deleeuw@gmail.com
Co-authored-by: Xuan Son Nguyen son@huggingface.co