MESHTEN LAB•Model Reviews
September 9, 2026•Model Evaluation

The Local Coder Ceiling: 100% on Single Functions, 0% on Multi-File Bug Fixes Under Default Config

Coordinate ascent benchmarks on 30B and 80B MoE models: 0/24 under the default config; across all configs, 7 of 8 repo tasks never passed, with task 003 passing 1/3 at the best config.

Core Finding:Can current consumer-run local coding models replace frontier cloud models for autonomous software engineering? In rigorous coordinate ascent benchmarks across 30B and 80B MoE models, we measured 100% pass rates on single functions and single-file refactors, but 0/24 under the default config on repository-level bug fixes. Across all tested configs, 7 of 8 repo tasks never passed; task 003 reached 1/3 at the best config (best-of-3, temp 0.6) and 3/3 under a surgical system prompt.

Tier 1: Single Function

30 / 30 (100%)

Both 30B and 80B MoE achieved perfect pass rates on isolated function edits.

Tier 2: Single File

12 / 12 (100%)

Flawless execution on multi-function refactors contained within a single file.

Tier 3: Repo Fixes (Default)

0 / 24 (0%)

0/24 under the default config (best_of_n=1, temp=0.2); across all configs, 7 of 8 repo tasks never passed, with task 003 passing 1/3 at best config (best-of-3, temp 0.6) and 3/3 under the surgical prompt.

In-VRAM Throughput

315-340 tok/s

30B achieved 315 to 340 tok/s decode; 80B MoE achieved 214 tok/s in VRAM.

Empirical Findings Table

Pass rates across task difficulty tiers on identical hardware
Telemetry MetricMeasured ValueContext & Observability
Tier 1: Single Function30 / 30 (100%)Both 30B and 80B MoE achieved perfect pass rates on isolated function edits.
Tier 2: Single File12 / 12 (100%)Flawless execution on multi-function refactors contained within a single file.
Tier 3: Repo Fixes (Default)0 / 24 (0%)0/24 under the default config (best_of_n=1, temp=0.2); across all configs, 7 of 8 repo tasks never passed, with task 003 passing 1/3 at best config (best-of-3, temp 0.6) and 3/3 under the surgical prompt.
In-VRAM Throughput315-340 tok/s30B achieved 315 to 340 tok/s decode; 80B MoE achieved 214 tok/s in VRAM.

Engineering Action Directives

  • Local coder models (30B and 80B MoE) have reached high reliability on single-function and single-file refactors, but drop precipitously when required to reason across multiple repository files.
  • Autonomous agent workflows should decompose large tasks into localized single-file subagent briefs when targeting local model execution.

Methodology Boundaries & Limits

  • Model sample: Evaluated on Qwen3-Coder-30B and Qwen3-Coder-Next-80B MoE; other open weight architectures may exhibit different tier boundaries.
  • Benchmark task set: 30 single-function tasks, 12 single-file tasks, and 24 repository-level tasks in our coordinate ascent harness; broader benchmark suites like SWE-bench provide additional difficulty gradations.