Changelog

High-level release notes for veloGB10. Minor bug fixes and small optimizations are grouped under generic language where they aren't individually notable.

v0.5.2 — vLLM-compatible tokenize / detokenize endpoints

• POST /v1/tokenize — vLLM-compatible tokenization: {tokens, count, max_model_len}, a pure tokenizer call (no forward / KV / GPU). Accepts a prompt string or a chat messages array; the messages mode renders exactly as the chat path so its count equals usage.prompt_tokens. Empty prompt → {tokens: [], count: 0}; over-length → 400 context_length_exceeded.
• POST /v1/detokenize — vLLM-compatible decode half of the pair ({model, prompt}) for exact-N prompt building.
• Added so our engine can be benchmarked more correctly. Minor bug fixes and optimizations.

v0.5.1 — Vision robustness, reasoning-effort, graceful-load fixes

• Vision generalization + boot fix. The GPU vision tower now bootstraps opportunistically: a non-vision or geometry-incompatible model serves text-only instead of crashing at startup (fixes a v0.5.0 boot crash on non-27B packs). Vision is generalized across the Qwen3.5/3.8 VL family, so all vision-tower models serve images.
• OpenAI reasoning_effort. Full level table (none/low/medium/high/xhigh/max) with per-family normalization, plus --reasoning-effort; the high mapping no longer silently drops thinking (regression fix).
• Tool-call + reasoning-mode fix. Tool-call markup is held back in reasoning mode too, fixing a first-call double-emit leak.
• Graceful model-load exit. Corrupted / stale / wrong-format checkpoints exit with a clear actionable message instead of a panic/OOM/core-dump.
• --output-prompts [n] — human-readable chat-request logging; --vision-cpu now listed in --help. Minor bug fixes and optimizations.

v0.5.0 — Vision support

• Vision support. Image input is now supported end-to-end on a GPU vision tower (gpu_vision kernels), with a --vision-cpu escape hatch to the CPU reference path. PNG/JPEG/WebP/GIF decoding added. The engine now ships and requires the gpu_vision.ptx kernel artifact in addition to the existing PTX set.
• Better tool-call support. A single canonical serializer now handles streaming and non-streaming tool-call output identically, repairs malformed tool-call tags, and no longer drops or leaks text around tool-call boundaries. New tool-call compliance and serializer test suites.
• Prefill/TTFT optimizations. New opt-in prefill levers (tensor-core flash-attention prefill, v2 W4A4 prefill GEMM, GDN tensor-core chunked scan), all env-gated default off, so the default serving path is unchanged. Minor bug fixes and optimizations.
• Model-id fix. /v1/models and responses now report the model card's base_model (e.g. Qwen/Qwen3.8-27B) instead of a local directory fragment. --model-name still overrides.

v0.4.2

• Fix: accept OpenAI multipart content (string | array | null) to unblock agent clients that send content parts; request-schema only.

v0.4.1

• Fix: --draft-dir is now mandatory only when --spec-source explicitly names a DFlash2 mode; plain-MTP launches no longer require it.

v0.4.0

• Qwen3.8 27B NVFP4 support with native DFlash 2 speculative decoding, full 256K context.
• TP=4 serving (plus TP=2 and single-node).
• New DSV4 / DFlash2 / DSpark / MXFP4 kernel set.
• README Update section with the Qwen3.8 27B performance table and live throughput traces; new QWEN_27B_SETUP.md and MANAGING_CACHE.md docs.

v0.3.1

• KAT-Coder model support; supported-models table in the README.

v0.3.0

• README generalization and load-pipeline features. Minor bug fixes and optimizations.

v0.2.0

• Tencent Hy3 (hy_v3) family support, 4-bit KV cache, FR-Spec draft head, model-name family fix.

v0.1.0

• Initial public release: from-scratch Rust + CUDA engine for Qwen3.5/3.6 on single and TP=2 GB10, with NVFP4/FP8 quantization, MTP speculative decoding, an OpenAI-compatible server, and prebuilt release binaries.