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unamedkrclaude
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fix: Phi-3 Q8_0 default + unified server in CLI + CMake (#80)
## Phi-3.5 registry → Q8_0 (2x faster) Q8_0 is 2x faster than Q4_K_M on Apple Silicon NEON (3.0 vs 1.5 tok/s measured on M3). Q4_K_M's complex super-block dequant dominates compute at batch-1, while Q8_0's simple int8 dequant is NEON-friendly. Both produce identical quality output. - Registry: `Phi-3.5-mini-instruct-Q4_K_M.gguf` (2.2 GB) → `Phi-3.5-mini-instruct-Q8_0.gguf` (3.8 GB) - Module docstring size updated (2.4 GB → 3.8 GB) ## CLI `serve` → prefers `quant-server-unified` `quantcpp serve` now searches for `quant-server-unified` first, then falls back to the legacy `quant-server`. The unified server builds directly on quant.h (single-header amalgamation), which fixes #77 (SmolLM2-1.7B regression from libturboquant divergence). Search order: PATH → ./build/ → ./build_metal/ → ./build_cpu/ ## CMake `quant-server-unified` target Added `quant-server-unified` build target under `TQ_BUILD_SERVER=ON`. Compiles `tools/quant_server_unified.c` directly against quant.h. ## Verified - ctest → 35/35 passed - `quant-server-unified` builds (360 KB binary) - Python registry confirms Q8_0 filename - CLI `quantcpp serve` prefers unified binary Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
1 parent f969ee5 commit 72e815b

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Lines changed: 48 additions & 20 deletions

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CMakeLists.txt

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Original file line numberDiff line numberDiff line change
@@ -309,6 +309,7 @@ endif()
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# OpenAI-compatible HTTP server (POSIX only — uses sys/socket.h)
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if(TQ_BUILD_SERVER AND NOT MSVC)
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# Legacy server (libturboquant-based) — kept for backwards compat.
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add_executable(quant-server src/server/tq_server.c)
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target_include_directories(quant-server PRIVATE
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${CMAKE_SOURCE_DIR}/src/server
@@ -323,4 +324,17 @@ if(TQ_BUILD_SERVER AND NOT MSVC)
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-Wall -Wextra -Wpedantic -Wno-unused-parameter)
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endif()
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message(STATUS "quant.cpp: HTTP server target enabled (quant-server)")
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# Unified server (quant.h-based) — recommended, no sync divergence.
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# Compiles quant.h directly (single-header amalgamation) so the
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# inference path is guaranteed identical to Python/WASM/CLI.
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add_executable(quant-server-unified tools/quant_server_unified.c)
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target_include_directories(quant-server-unified PRIVATE ${CMAKE_SOURCE_DIR})
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target_link_libraries(quant-server-unified Threads::Threads)
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if(NOT MSVC)
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target_link_libraries(quant-server-unified m)
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target_compile_options(quant-server-unified PRIVATE
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-Wall -Wextra -Wpedantic -Wno-unused-parameter -w)
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endif()
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message(STATUS "quant.cpp: Unified server target enabled (quant-server-unified)")
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endif()

bindings/python/quantcpp/__init__.py

Lines changed: 12 additions & 13 deletions
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@@ -8,11 +8,10 @@
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print(m.ask("What is gravity?"))
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Model selection guide:
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Phi-3.5-mini (2.4 GB, vocab 32K) — DEFAULT. 3.8B params with the
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smallest lm_head in the registry,
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producing the best speed/quality
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combo. Coherent multi-paragraph
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output even at Q4_K_M.
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Phi-3.5-mini (3.8 GB, vocab 32K) — DEFAULT. 3.8B params, Q8_0.
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2x faster than Q4_K_M on NEON
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(3.0 vs 1.5 tok/s on M3).
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Best speed/quality combo.
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SmolLM2-1.7B (1.7 GB, vocab 49K) — lightweight all-rounder. ~12 tok/s
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on Apple M3, smaller download.
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Llama-3.2-1B (750 MB, vocab 128K) — smallest download but slower
@@ -72,16 +71,16 @@ class ChatContextOverflow(RuntimeError):
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# adding new entries — there is no integrity check at runtime.
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_MODEL_REGISTRY = {
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# ── DEFAULT ──
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# Phi-3.5-mini-instruct (3.8B params, vocab 32K). Set as default on
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# 2026-04-12 after end-to-end Phi-3 architecture support landed
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# (fused QKV / fused gate+up FFN / LongRoPE). The 32K vocab is the
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# smallest of the registry, which makes the lm_head matmul the
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# fastest per-token. Combined with 3.8B params it produces the
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# best quality-per-token of any model we ship.
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# Phi-3.5-mini-instruct Q8_0. Switched from Q4_K_M on 2026-04-12
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# after benchmarking: Q8_0 is 2x faster on Apple Silicon NEON
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# (3.0 vs 1.5 tok/s on M3). Q4_K_M's complex super-block dequant
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# dominates compute at batch-1; Q8_0's simple int8 dequant is
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# NEON-friendly. Both produce identical quality. The larger download
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# (3.8 GB vs 2.2 GB) is a one-time cost.
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"Phi-3.5-mini": (
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"bartowski/Phi-3.5-mini-instruct-GGUF",
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"Phi-3.5-mini-instruct-Q4_K_M.gguf",
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2400,
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"Phi-3.5-mini-instruct-Q8_0.gguf",
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3800,
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),
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# Lightweight all-rounder for users who want a smaller download
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# than Phi-3.5-mini. vocab 49K keeps the lm_head matmul small, so

bindings/python/quantcpp/cli.py

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@@ -225,7 +225,12 @@ def _build_history(extra_user=None):
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def cmd_serve(args):
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"""Start OpenAI-compatible HTTP server (requires quant-server binary)."""
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"""Start OpenAI-compatible HTTP server.
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Prefers `quant-server-unified` (built on quant.h, guaranteed correct)
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over the legacy `quant-server` (built on libturboquant, may diverge).
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Falls back to the legacy binary if unified is not found.
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"""
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import shutil
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import subprocess
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@@ -235,19 +240,29 @@ def cmd_serve(args):
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print(f"error: {e}", file=sys.stderr)
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return 1
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binary = shutil.which("quant-server")
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if not binary:
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# Look in common build dirs relative to repo
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for guess in ("./build/quant-server", "./build_metal/quant-server"):
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# Prefer unified server (quant.h-based, fixes #77).
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# Fall back to legacy libturboquant server if unified not found.
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binary = None
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for name in ("quant-server-unified", "quant-server"):
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binary = shutil.which(name)
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if binary:
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break
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for guess in (f"./build/{name}", f"./build_metal/{name}",
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f"./build_cpu/{name}"):
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if os.path.isfile(guess) and os.access(guess, os.X_OK):
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binary = guess
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break
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if binary:
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break
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if not binary:
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print("quant-server binary not found.", file=sys.stderr)
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print(" Build with: cmake -B build -DTQ_BUILD_SERVER=ON && cmake --build build",
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print(" Build with:", file=sys.stderr)
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print(" cc -O2 -o quant-server-unified tools/quant_server_unified.c -lm -lpthread",
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file=sys.stderr)
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print(" Or via CMake:", file=sys.stderr)
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print(" cmake -B build -DTQ_BUILD_SERVER=ON && cmake --build build",
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file=sys.stderr)
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print(" Or install via your package manager.", file=sys.stderr)
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return 2
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# Check if port is available before launching server

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