Steelman R5: Fine-tuned 14B Model Outperforms Claude Opus on Ada Code Generation

Model and Training Details
The Steelman R5 model is a fine-tuned version of Qwen2.5-Coder-14B-Instruct specifically optimized for Ada code generation. Training used QLoRA 4-bit via Unsloth with TRL SFTTrainer on a dataset of 3,430 Ada/SPARK instruction pairs where every training example passes gnatmake -gnat2022 -gnatwa compilation.
Training configuration: LoRA rank 32, alpha 64, targeting q/k/v/o/gate/up/down projections. The model was fully retrained from base each round on accumulated dataset (adapter continuation caused catastrophic forgetting at R2). Training ran for 1 epoch with learning rate 2e-5, constant schedule, taking about 49 minutes per round on a rented H100. Five rounds total (R1–R5), with R2 discarded.
Benchmark Results
Custom Ada Compilation Benchmark (1,000 prompts, first-attempt clean compile):
- Steelman R5 (14B): 68.6% compile rate
- Claude Opus 4.6: 42.1% compile rate
- Claude Sonnet 4.6: 37.2% compile rate
- Qwen2.5-Coder-14B (base, untuned): ~35% compile rate
- Claude Sonnet 4: 27.5% compile rate
MultiPL-E HumanEval-Ada (157 problems, pass@1):
- Steelman R5: 47.1% pass@1, 74.5% compile rate
- Qwen2.5-Coder-14B (base): 34.4% pass@1, 51.0% compile rate
These are the first published Ada pass@1 results on HumanEval for any open model.
Usage and Availability
Run the model with: ollama run hf.co/the-clanker-lover/steelman-14b-ada-v0.1-GGUF
The GGUF version fits in 12GB VRAM with Q4_K_M quantization.
Limitations
- Compilation ≠ correctness: 68.6% compiles, but only 47.1% produces correct output on HumanEval
- Error-fix capability is weak (5.1%) - don't expect it to debug Ada code
- SPARK contracts compile but aren't verified with gnatprove
- Synthetically generated training data - no human Ada developers wrote these examples
- 14B model size means it may miss things a larger model would catch
Resources
- Model: https://huggingface.co/the-clanker-lover/steelman-14b-ada-v0.1
- GGUF: https://huggingface.co/the-clanker-lover/steelman-14b-ada-v0.1-GGUF
- Dataset: https://huggingface.co/datasets/the-clanker-lover/steelman-sft-ada
📖 Read the full source: r/LocalLLaMA
👀 See Also

Stoa Markets: A Marketplace for GPUs and AI Servers with Verified Quotes
Stoa is a marketplace for buying and selling new and used GPUs and AI servers. It standardizes RFQs, verifies counterparties, and provides firm quotes, aiming to improve price discovery in the GPU market.

OpenClaw Agent Memory Plugin: Persistent Context Across Sessions
A developer built a memory layer plugin for OpenClaw that injects relevant context from past conversations before each turn and stores new facts and events after each turn, solving the problem of agents forgetting everything between sessions.

VidLens MCP Server: Persistent YouTube Knowledge Base for Claude
VidLens is a free, open-source MCP server that indexes YouTube content locally with semantic embeddings, treating videos as a persistent knowledge base rather than extracting temporary transcripts. It provides 41 tools across 10 modules for searching, analyzing, and retrieving video content.

nex-life-logger: Local Activity Tracker for OpenClaw Agents
nex-life-logger is a background activity tracker that runs locally on your machine, giving OpenClaw agents memory of your computer activities. It tracks browser history, active windows, and YouTube transcripts, storing everything in a local SQLite database with no cloud data transmission.