Prism Coder 27B — Qwen3.5-27B Function-Calling Model
Fine-tuned from Qwen3.5-27B for MCP tool-routing. Part of the Prism Coder fleet.
Performance
| Metric | Value |
|---|---|
| BFCL Accuracy | 100% × 3 seeds (345/345 test cases) |
| Raw accuracy | 100% (no L3 correction needed) |
| Tokens/sec (Q4_K_M, M5 48GB) | 28.5 |
| GGUF Q4_K_M size | 16 GB |
| Architecture | Hybrid DeltaNet (48/64 layers) + GQA (16/64) |
| Long context | O(n) via recurrent DeltaNet state |
Training
| Parameter | Value |
|---|---|
| Base model | Qwen/Qwen3.5-27B |
| Method | QLoRA (4-bit NF4) |
| LoRA rank | 128, alpha=256 |
| Target modules | q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj |
| Layers | All 64 (including DeltaNet) |
| Training data | 24,798 examples (AAC 54%, tool-use 25%, safety 8%, abstention 8%) |
| Hardware | NVIDIA H100 PCIe 80GB |
| Duration | 12.5 hours |
| Final loss | 0.25 |
| Token accuracy | 93.2% |
| Cost | ~$29 |
Fleet
| Tag | Size | BFCL | Role |
|---|---|---|---|
prism-coder:2b |
2.3 GB | 99.1% | Mobile / iPhone |
prism-coder:4b |
3.4 GB | 100% | Verifier |
prism-coder:9b |
5.8 GB | 100% | Default router |
prism-coder:27b |
16 GB | 100% | Quality tier |
Usage
ollama pull dcostenco/prism-coder:27b
ollama run dcostenco/prism-coder:27b "Load context for the analytics project"
Or via the Prism MCP server:
{"mcpServers": {"prism": {"command": "npx", "args": ["-y", "prism-mcp-server"]}}}
License
Apache 2.0 (same as base model)