v0.1.2

• Fixed the adaptive profit controller's no-spec baseline path. Profit mode now seeds baseline samples before positive-depth warmup, can shut DFlash fully off when the measured baseline wins, and no longer makes speculative decisions from draft-only telemetry.
• Fixed profit-controller reset handling across context-bucket and configuration changes so cleared baseline telemetry cannot leave the controller in a stale active or off state.
• Added low-frequency profit-controller baseline reprobes with --spec-dm-profit-baseline-interval / LLAMA_ARG_SPEC_DM_PROFIT_BASELINE_INTERVAL so runs can refresh target-only timing as context grows. The default interval is 1024 active speculative cycles; reprobes resume the previous active draft depth and avoid off-probe counter starvation.
• Hardened active-reasoning EOS handling. When an end-of-generation token appears while reasoning output is still active, the sampler now forces the reasoning-end sequence through the normal full-logits path; reduced DFlash verification rejects that case instead of accepting an unsafe reduced candidate set.
• Hardened DFlash on split CUDA / multi-GPU placement. GPU cross-ring setup, hidden capture, CUDA graph capture, K/V projection cache updates, recurrent replay, conv replay, and async tensor get/set paths now check buffer/backend ownership and fall back to safer CPU or owning-buffer paths instead of reading or writing recurrent state through the wrong CUDA backend.
• Added clearer diagnostics and regression coverage for multi-GPU DFlash fallback decisions, CUDA graph buffer visibility, wrong-device async tensor access, active-reasoning reduced-sampling rejection, adaptive DM defaults, and profit-controller baseline behavior.
• Fixed ROCm 7 build: added cudaPointerAttributes / cudaMemoryType shim aliases to hip.h, extended CUDART_VERSION >= 10000 guards with || defined(GGML_USE_HIP) so the .type field path is taken on HIP, and removed the WIN32 guard around TurboQuant flash-attention instance compilation so Linux ROCm builds include the turbo KV-cache kernels (acerspyro#11).
• Known limitation: the current multi-GPU DFlash path is a correctness fallback, not a performant split-GPU implementation. On split target placement it can be slower than non-speculative decoding because recurrent replay and hidden capture avoid unsafe single-backend GPU fast paths. A performant implementation still needs per-device replay graphs or a scheduler that follows ggml's split-buffer ownership model.

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Windows:

• Windows x64 (CUDA 12) - CUDA 12.4 DLLs
• Windows x64 (CUDA 13) - CUDA 13.1 DLLs

v0.1.1

• Improved agentic tool-call reliability with lazy grammars. DFlash now remains enabled before a lazy grammar trigger, but stops speculating once grammar-constrained output or reasoning-budget forcing requires normal token-by-token sampling.
• Fixed DFlash accept bookkeeping at grammar and tool-call boundaries. The server now distinguishes accepted draft tokens from bonus-token-shaped results, updates DFlash hidden-state rows with the root plus accepted draft tokens, and uses the same keep count for rollback.
• Added a DFlash suppression guard for raw tool-call markers. When a tool marker appears while lazy grammar is enabled, the server suppresses DFlash for the rest of that response without steering sampler state; fenced code and embedded marker-like strings are excluded from the guard.
• Made partial OpenAI-compatible tool-call streaming safer. The server can stream a stable tool name/id early so clients can show a pending tool call, while withholding partial arguments until the parser sees a complete call.
• Quarantined malformed raw tool-call text in tool-parsing streams. Unfinished or malformed tool-looking text no longer leaks into visible assistant content or hidden reasoning deltas before the parser can classify it.
• Accepted direct tag-style function starts for Qwen-style tool calls. Lazy grammar triggers now include structural function markers such as <function=, and the tag parser can parse valid direct function calls without the outer <tool_call> wrapper.
• Added regression coverage for Kimi and Qwen tool-call streaming, malformed raw marker quarantine, fenced-code false positives, direct Qwen function calls, lazy grammar triggers, and DFlash speculative boundary plumbing.
• Fixed small build issues found after 0.1.0: the DFlash callback setup now uses an explicit callback type for GCC 15, and tests/server code include the required standard headers for INT_MAX and FLT_MAX.

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Windows:

• Windows x64 (CUDA 12) - CUDA 12.4 DLLs
• Windows x64 (CUDA 13) - CUDA 13.1 DLLs

v0.1.0

• DFlash speculative decoding: --spec-type dflash drives a DFlash draft GGUF alongside the target model. The target captures hidden states into a per-layer 4096-slot ring buffer, the drafter cross-attends to the most recent --spec-dflash-cross-ctx hidden-state tokens and proposes drafts for target verification.
• TurboQuant / TCQ KV-cache compression: Five cache types (turbo2, turbo3, turbo4, turbo2_tcq, turbo3_tcq) spanning from 4x to 7.5x compression, with higher-bit options being practically lossless in many cases. Set independently with --cache-type-k and --cache-type-v.
• Adaptive draft-max control: The server adjusts the active draft horizon at runtime instead of using a fixed --spec-draft-n-max. The default profit controller compares speculative throughput against a no-spec baseline; the fringe alternative maps acceptance-rate bands to draft depth. Use --no-spec-dm-adaptive for a static horizon.
• Full multimodal support: When --mmproj is active, the server keeps flat DFlash available for text generation. The model can be fully offloaded to CPU with no problems to reduce VRAM pressure.
• Reasoning-loop protection: The server detects repeated hidden reasoning output and intervenes. Default mode is force-close with --reasoning-loop-window and --reasoning-loop-max-period tuning available.
• Sampled DFlash verification: --spec-draft-temp enables rejection-sampling drafter behavior. Activates when both draft and target temperature exceed zero. Draft log probabilities must be available for rejection sampling to produce correct output.
• DDTree branch verification: optional --spec-branch-budget adds branch nodes beyond the main draft path with GPU parent_ids, tree masks, and recurrent tree kernels. Disabled automatically when the target model spans more than one GPU. This one is very much work in progress!
• Request-level speculative overrides: Draft-max and branch budget can be overridden per-request through JSON fields without restarting the server.
• CopySpec model-free speculation: --spec-type copyspec provides rolling-hash suffix matching over previous tokens without a draft model. Results must be benchmarked per workload.

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Windows:

• Windows x64 (CUDA 12) - CUDA 12.4 DLLs
• Windows x64 (CUDA 13) - CUDA 13.1 DLLs