Flint — APEX quants
Upload in progress. The 5 bpw GGUF is uploading now; 4 bpw and 3 bpw are queued behind it, followed by their recipes and the imatrix. This note will be removed once all three quants are present.
APEX quant ladder for RecursiveSI/flint, a 39.8B-total / ~2.5B-active MoE coding agent from Recursive (Apache 2.0). Weights are quantized with llama.cpp and evaluated with the 42-task OpenCode agentic suite.
Tiers
| tier | file | size | effective bpw | status |
|---|---|---|---|---|
| 5 bpw | Recursive-Flint-APEX-5bpw.gguf |
23 GB | 4.76 | uploading |
| 4 bpw | Recursive-Flint-APEX-4bpw.gguf |
19 GB | 3.95 | queued |
| 3 bpw | Recursive-Flint-APEX-3bpw.gguf |
14 GB | 2.99 | queued |
Recipes (Flint-5bpw.recipe, Flint-4bpw.recipe, Flint-3bpw.recipe) and the code-weighted
imatrix are included as they finish uploading. The 4/3 bpw recipes use IQ expert types and the
imatrix computed against the 5 bpw artefact; the 5 bpw tier was built structurally.
42-task result (5 bpw)
Full OpenCode agentic-coding sweep on the GB10, temp 1.0, top_p 0.95, top_k 20, context
262144, output cap 32768, reasoning high, one slot, compaction off.
| suite | result |
|---|---|
opencode_tasks |
25/25 |
opencode_tasks_hard |
5/5 |
opencode_tasks_frontier |
9/9 |
opencode_tasks_tier4a |
3/3 |
| total | 42/42 (100%) |
Peak context used 120,829 / 262,144; zero voids and zero truncated slots. The result row and plots are in the APEX benchmark report.
Architecture
- 39.8B total / ~2.5B active decoder-only MoE
- 49 layers: 2 dense + 47 MoE; 256 routed experts (top-6) + 1 shared per MoE layer
- 35 sliding-window attention layers (window 513) + 14 full-attention layers
- GQA 32 query / 4 KV heads, head dim 128, per-head QK RMSNorm and learned attention sinks
- RoPE on sliding layers; no positional encoding on full-attention layers
- 262,144-token context, 150,144 vocab
Attribution
- Base model: Recursive, RecursiveSI/flint, Apache 2.0.
- Quantization and evaluation: this repository; llama.cpp.