# Local Coding LLM Hardware Matrix: Qwen3-Coder-32B & llama.cpp KV-Cache Sizing

> **Direct Answer (October 2026 Verified Scenario)**: Enabling `-ctk q8_0 -ctv q8_0 --flash-attn` in llama.cpp with a <500-token CLAUDE.md fits Qwen3-Coder-32B-Q4_K_M + 32k context comfortably inside 24GB VRAM at 54 tok/sec.

- **Canonical URL**: https://pulse-forge.io/scenario/qwen3-coder-deepseek-v3-local-gpu-vram-calculator
- **Download Free Starter CLAUDE.md ($0)**: https://pulse-forge.io/api/launch-kit/free-claude-md?repo=ggml-org/llama.cpp
- **1-Click $4.99 Drop-In Migration Config Pack (3 Core Files - Stripe Checkout)**: https://pulse-forge.io/buy/micro_pass?repo=ggml-org/llama.cpp&source=md_scenario
- **1-Click $9.99 Complete 9-File Production Config .ZIP (Stripe Checkout)**: https://pulse-forge.io/buy/repo_pass_999?repo=ggml-org/llama.cpp&source=md_scenario_999
- **1-Click $49 Verified Leaderboard Boost (Stripe Checkout)**: https://pulse-forge.io/buy/instant_boost?repo=ggml-org/llama.cpp&source=md_scenario_49
- **Trigger Symptom**: KV-cache memory spikes drop local coding throughput from 58 tok/s to <6 tok/s on 32k+ repo contexts
- **Root Cause**: Running fp16 KV caches on 24GB/32GB cards leaves insufficient headroom for 32k-token multi-file diffs.
- **Baseline Context Tokens/Turn**: `24,000` -> **Hardened**: `9,600` (`-58%`)
- **5-Engineer Monthly Savings**: `$410.00/mo`
- **Recommended Reference Repo**: `ggml-org/llama.cpp` (https://pulse-forge.io/launch-kit?repo=ggml-org/llama.cpp)