[claude] Qwen3 two-model strategy: 14B primary + 8B fast router (#1063) #1143

claude · 2026-03-23T18:35:20Z

claude commented

2026-03-23 18:35:20 +00:00

Fixes #1063

What this does

Translates the M3 Max 36 GB model selection study into production-ready artifacts.

New files

Modelfile.qwen3-14b — Primary agent model (Qwen3-14B Q5_K_M, 32K ctx, temp 0.3). Tool calling F1 0.971 — GPT-4-class reliability. ~17.5 GB total on M3 Max, leaving ~10.5 GB headroom. Hybrid thinking/non-thinking via /think and /no_think.
Modelfile.qwen3-8b — Fast routing model (Qwen3-8B Q6_K, 32K ctx, temp 0.2). Tool calling F1 0.933 at ~45–55 tok/s. ~11.6 GB total. Combined with 14B: ~17 GB — both stay loaded simultaneously with OLLAMA_MAX_LOADED_MODELS=2.
scripts/benchmark_local_model.sh — 5-test evaluation suite from the study:
1. Tool call compliance (≥90% valid JSON via Ollama chat API)
2. Code generation (valid Python syntax check)
3. Shell command generation (no refusal markers)
4. Multi-turn agent loop coherence (session ID echo)
5. Issue triage quality (structured JSON with required fields)

Config changes (`src/config.py`)

Setting	Before	After	Reason
`ollama_model`	`qwen3:30b`	`qwen3:14b`	30B exceeds memory budget at 32K ctx on 36 GB
`ollama_num_ctx`	`4096`	`32768`	14B fits at 32K; 4096 was a workaround for 30B
`ollama_fast_model`	(new)	`qwen3:8b`	Fast routing for routine tasks
`ollama_max_loaded_models`	(new)	`2`	Keep both models hot simultaneously
`fallback_models[0]`	`llama3.1:8b-instruct`	`qwen3:8b`	Better tool calling than llama3.1

Test plan

tox -e unit — 20/20 tests pass
ollama create qwen3-14b -f Modelfile.qwen3-14b && ollama create qwen3-8b -f Modelfile.qwen3-8b
./scripts/benchmark_local_model.sh qwen3:14b qwen3:8b

🤖 Generated with Claude Code

Fixes #1063 ## What this does Translates the M3 Max 36 GB model selection study into production-ready artifacts. ### New files - **`Modelfile.qwen3-14b`** — Primary agent model (Qwen3-14B Q5_K_M, 32K ctx, temp 0.3). Tool calling F1 0.971 — GPT-4-class reliability. ~17.5 GB total on M3 Max, leaving ~10.5 GB headroom. Hybrid thinking/non-thinking via `/think` and `/no_think`. - **`Modelfile.qwen3-8b`** — Fast routing model (Qwen3-8B Q6_K, 32K ctx, temp 0.2). Tool calling F1 0.933 at ~45–55 tok/s. ~11.6 GB total. Combined with 14B: ~17 GB — both stay loaded simultaneously with `OLLAMA_MAX_LOADED_MODELS=2`. - **`scripts/benchmark_local_model.sh`** — 5-test evaluation suite from the study: 1. Tool call compliance (≥90% valid JSON via Ollama chat API) 2. Code generation (valid Python syntax check) 3. Shell command generation (no refusal markers) 4. Multi-turn agent loop coherence (session ID echo) 5. Issue triage quality (structured JSON with required fields) ### Config changes (`src/config.py`) | Setting | Before | After | Reason | |---|---|---|---| | `ollama_model` | `qwen3:30b` | `qwen3:14b` | 30B exceeds memory budget at 32K ctx on 36 GB | | `ollama_num_ctx` | `4096` | `32768` | 14B fits at 32K; 4096 was a workaround for 30B | | `ollama_fast_model` | _(new)_ | `qwen3:8b` | Fast routing for routine tasks | | `ollama_max_loaded_models` | _(new)_ | `2` | Keep both models hot simultaneously | | `fallback_models[0]` | `llama3.1:8b-instruct` | `qwen3:8b` | Better tool calling than llama3.1 | ## Test plan - [x] `tox -e unit` — 20/20 tests pass - [ ] `ollama create qwen3-14b -f Modelfile.qwen3-14b && ollama create qwen3-8b -f Modelfile.qwen3-8b` - [ ] `./scripts/benchmark_local_model.sh qwen3:14b qwen3:8b` 🤖 Generated with [Claude Code](https://claude.com/claude-code)

claude added 1 commit 2026-03-23 18:35:21 +00:00

feat: implement Qwen3 two-model strategy from M3 Max model study

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Details

59ccb382aa

Translates findings from the M3 Max 36 GB model selection study (Issue #1063)
into production-ready config and tooling artifacts.

Changes:
- Modelfile.qwen3-14b: primary agent model (Q5_K_M, 32K ctx, temp 0.3)
  Tool calling F1 0.971, ~17.5 GB total — fits M3 Max with 10 GB headroom
- Modelfile.qwen3-8b: fast routing model (Q6_K, 32K ctx, temp 0.2)
  Tool calling F1 0.933 at ~45-55 tok/s; ~11.6 GB total
- scripts/benchmark_local_model.sh: 5-test evaluation suite
  Tests tool call compliance, code gen, shell gen, multi-turn coherence,
  and issue triage quality with pass/fail thresholds
- config.py: update defaults for M3 Max 36 GB hardware
  - ollama_model: qwen3:30b → qwen3:14b (within memory budget at 32K ctx)
  - ollama_fast_model: new field, defaults to qwen3:8b
  - ollama_max_loaded_models: new field, defaults to 2 (both models hot)
  - ollama_num_ctx: 4096 → 32768 (qwen3:14b fits at 32K; 30b did not)
  - fallback_models: promote qwen3:8b as first fallback

Refs #1063

claude referenced this pull request

2026-03-23 18:35:32 +00:00

[Study] Best Local Uncensored Agent Model for M3 Max 36GB #1063

claude merged commit ed63877f75 into main

2026-03-23 18:35:58 +00:00

claude deleted branch claude/issue-1063

2026-03-23 18:35:58 +00:00

claude referenced this issue from a commit

2026-03-23 18:35:58 +00:00

[claude] Qwen3 two-model strategy: 14B primary + 8B fast router (#1063) (#1143)

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