OpenAgentsControl/docs/model-providers/oss/LM-STUDIO-SETUP.md

LM Studio Optimal Settings for OpenCode

This guide provides battle-tested configurations for running Qwen3-Coder and GPT-OSS-20B with OpenCode via LM Studio.

Quick Start

1. Copy the configuration from lmstudio-config-example.json to your opencode.json
2. Download your models in LM Studio
3. Start the LM Studio server on port 1234
4. Launch OpenCode and use /models to select your local model

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Model-Specific Settings

Qwen3-Coder-30B (Recommended Primary Model)

Best for: Precise tool calling, code generation, debugging

{
  "limit": {
    "context": 24000,
    "output": 4000
  },
  "options": {
    "temperature": 0.1,
    "topP": 0.8,
    "minP": 0.01,
    "repetitionPenalty": 1.05
  }
}

Why these settings:

• Temperature 0.1: Maximizes deterministic tool calling reliability. Use 0.2-0.3 for more creative exploration.
• Top-P 0.8: Constrains token diversity appropriately for coding tasks
• Min-P 0.01: Lower than llama.cpp default (0.1) for better tool use
• Repetition Penalty 1.05: Prevents infinite loops during multi-step tool calls
• Context 24000: Handles large codebases without frequent compaction
• Output 4000: Sufficient for most code generation tasks

GPT-OSS-20B (Alternative/Backup Model)

Best for: General coding, conversation, when you need higher creativity

{
  "limit": {
    "context": 16000,
    "output": 4000
  },
  "options": {
    "temperature": 0.4,
    "topP": 0.9,
    "minP": 0.05,
    "repetitionPenalty": 1.05
  }
}

Why these settings:

• Temperature 0.4: Higher than Qwen3 due to different architecture - still reliable for tools
• Top-P 0.9: More diversity for MoE (Mixture of Experts) architecture
• Min-P 0.05: Slightly higher for better creative balance
• Repetition Penalty 1.05: Same as Qwen3 for loop prevention
• Context 16000: Sufficient for most tasks, adjust based on VRAM

---

LM Studio Application Settings

GPU Acceleration (Critical)

In LM Studio Settings → Hardware:

1. GPU Offload Layers: Set to MAXIMUM your GPU can handle

   • RTX 4060 8GB: 36 layers
   • RTX 4070 12GB: 40 layers
   • RTX 4090 24GB: All layers
   • Mac M1/M2/M3: All layers (MLX preferred)

2. Keep Model in VRAM: ✅ Enable

3. Offload KV Cache to GPU: ✅ Enable (4x speedup on compatible hardware)

Context Settings

• Context Length: Match or exceed your config (24000 for Qwen3, 16000 for GPT-OSS)
• Batch Size: 512 (default) or higher if VRAM allows
• Threads: Set to CPU cores - 2 (e.g., 14 threads for 16-core CPU)

Speculative Decoding (Advanced)

For 30B+ models, enable speculative decoding:

• Draft Model: Use a small 1-3B model from the same family
• Speedup: 1.5x-3x without quality loss

---

OpenCode Integration

Full Configuration Example

{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "lmstudio": {
      "npm": "@ai-sdk/openai-compatible",
      "name": "LM Studio (Local)",
      "options": {
        "baseURL": "http://127.0.0.1:1234/v1"
      },
      "models": {
        "qwen3-coder-30b": {
          "name": "Qwen3-Coder-30B (Local)",
          "tools": true,
          "limit": {
            "context": 24000,
            "output": 4000
          },
          "options": {
            "temperature": 0.1,
            "topP": 0.8,
            "minP": 0.01,
            "repetitionPenalty": 1.05
          }
        },
        "gpt-oss-20b": {
          "name": "GPT-OSS-20B (Local)",
          "tools": true,
          "limit": {
            "context": 16000,
            "output": 4000
          },
          "options": {
            "temperature": 0.4,
            "topP": 0.9,
            "minP": 0.05,
            "repetitionPenalty": 1.05
          }
        }
      }
    }
  },
  "model": "lmstudio/qwen3-coder-30b",
  "agents": {
    "build": {
      "mode": "primary",
      "description": "Main build agent"
    }
  }
}

Switching Models

Use the /models command in OpenCode to switch between your configured models without restarting.

---

Troubleshooting

Tool Calls Not Working

1. Increase context window in LM Studio to 16k-32k minimum
2. Verify temperature is set correctly (0.1 for Qwen3, 0.4 for GPT-OSS)
3. Check repetition penalty is set to 1.05
4. Restart LM Studio server after changing settings

Slow Performance

1. Maximize GPU layers - check LM Studio logs for "offloaded X/Y layers"
2. Enable KV cache offload in GPU settings
3. Reduce context length if hitting VRAM limits
4. Try speculative decoding with a draft model

Out of Memory

1. Reduce context length: 16000 → 12000 → 8000
2. Reduce GPU layers: Start at 50% and increase
3. Switch to smaller quantization: Q6 → Q5 → Q4
4. Close other applications using VRAM

Model Repeating Itself

1. Increase repetition penalty: 1.05 → 1.10 → 1.15
2. Lower temperature slightly: 0.1 → 0.05
3. Check min-P setting: Should be 0.01-0.05

---

Hardware Recommendations

Minimum Specs (Qwen3-Coder-30B)

• GPU: 12GB VRAM (RTX 4070, RTX 3080 12GB)
• RAM: 16GB system RAM
• Quantization: Q4_K_M or Q5_K_M

Recommended Specs (Qwen3-Coder-30B)

• GPU: 16-24GB VRAM (RTX 4080, RTX 4090)
• RAM: 32GB system RAM
• Quantization: Q6_K or Q8

Minimum Specs (GPT-OSS-20B)

• GPU: 8GB VRAM (RTX 4060)
• RAM: 16GB system RAM
• Quantization: Q4_K_M

Mac Users

• MLX versions strongly recommended over GGUF
• Significantly faster on Apple Silicon
• Use LM Studio's MLX support or native MLX inference
• M1/M2/M3 with 16GB+ unified memory works well

---

Performance Expectations

Qwen3-Coder-30B (Q5_K_M on RTX 4080)

• Tokens/second: 15-25 t/s
• Context loading: 2-3 seconds
• Tool call reliability: 95%+

GPT-OSS-20B (Q5_K_M on RTX 4060)

• Tokens/second: 20-30 t/s
• Context loading: 1-2 seconds
• Tool call reliability: 90%+

---

Settings Comparison Table

Setting	Qwen3-Coder	GPT-OSS-20B	Reasoning
Temperature	0.1	0.4	Qwen3 needs lower for tool calling
Top-P	0.8	0.9	MoE models benefit from more diversity
Min-P	0.01	0.05	Lower for deterministic tool use
Repetition Penalty	1.05	1.05	Prevents loops in both
Context	24000	16000	Qwen3 handles larger contexts better
Output	4000	4000	Standard for code generation

---

When to Adjust Settings

For More Creativity

• Increase temperature: 0.1 → 0.3 (Qwen3) or 0.4 → 0.6 (GPT-OSS)
• Increase top-P: 0.8 → 0.9 or 0.9 → 0.95

For More Precision

• Decrease temperature: 0.1 → 0.05 (careful: may reduce quality)
• Decrease top-P: 0.8 → 0.7

For Handling Repetition

• Increase repetition penalty: 1.05 → 1.10
• Add frequency penalty: 0 → 0.3

---

Notes

• These settings are optimized for tool calling reliability with OpenCode
• Raw performance benchmarks show Ollama may be faster, but tool calling is unreliable
• LM Studio's proper parameter handling makes it the recommended choice for OpenCode
• Settings can be adjusted per-use-case, but these defaults work for 90% of coding tasks