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ContentsAppendix B

Appendix BCase study: small models in a coding harness

Cost and time

The same passing result cost from a fraction of a cent to about 25 cents, and bigger wasn't leaner.

Cost of one passing run, US dollars at the price recorded for each route, log scale. Each step on the scale is ten times the last.

Small cloud models

  • grok-4-1-fast-non-reasoning$0.003
  • gpt-6-luna$0.0039
  • grok-4-1-fast-reasoning$0.004
  • DeepSeek-V4-Flash$0.011
  • gpt-5.6-luna$0.011
  • gpt-5.4-nano$0.014
  • gemini-3.5-flash-lite$0.02
  • claude-haiku-4-5$0.03
  • gemini-3.5-flash$0.059
  • gpt-5.4-mini$0.06
  • gemini-3.8-flash$0.077

Frontier models

  • Mistral-Large-3$0.03
  • gpt-6-sol$0.03
  • DeepSeek-V4-Pro$0.036
  • gpt-4.1$0.037
  • kimi-k2.6$0.045
  • grok-4.3$0.049
  • claude-sonnet-5$0.063
  • gpt-5$0.097
  • claude-opus-4-6$0.15
  • claude-sonnet-4-6$0.15
  • grok-4-20-non-reasoning$0.21
  • DeepSeek-V3.2$0.25

The one local pass isn't shown: local models have no per-token price.

Why can a job of under 100 lines cost 25 cents? A model doesn't remember between steps, so the harness re-sends the whole conversation every round.1 Runs read 16,000 to 578,000 tokens of input (a token is a word or part of a word). In a typical cloud run about 74% of that was served from the vendor's cache at a lower rate;2 the most expensive run, DeepSeek V3.2, got no cache discount at all. Bigger also wasn't leaner: 6 models finished in 3 tool calls, while grok-4-20-non-reasoning, a frontier model, made 36 for the same job.

Go deeper: how long each run took
How long each run took, start to finish, every model. Hollow bars failed.

Small cloud models

  • Phi-4-mini-reasoning3 s · fail
  • grok-4-1-fast-non-reasoning17 s
  • claude-haiku-4-521 s
  • gemini-3.5-flash22 s
  • gemini-3.5-flash-lite23 s
  • gemini-3.1-flash-lite27 s · fail
  • gemini-3.8-flash31 s
  • DeepSeek-V4-Flash36 s
  • gpt-5.4-mini38 s
  • gpt-6-luna41 s
  • gpt-5.6-luna42 s
  • gpt-5.4-nano53 s
  • grok-4-1-fast-reasoning117 s

Local, downloadable models

  • qwen3-coder:30b50 s
  • qwen2.5-coder 1.5B197 s · fail
  • gpt-oss:20b529 s · fail
  • gemma3:27b550 s · fail

Frontier models

  • gpt-4.112 s
  • Mistral-Large-320 s
  • kimi-k2.621 s
  • claude-sonnet-521 s
  • DeepSeek-V4-Pro22 s
  • grok-4.330 s
  • gpt-6-sol34 s
  • claude-opus-4-641 s
  • claude-sonnet-4-675 s
  • DeepSeek-V3.282 s
  • gpt-583 s
  • grok-4-20-non-reasoning91 s
Notes (2)
  1. 1Anthropic, “Effective context engineering for AI agents,” Anthropic Engineering, September 29, 2025, https://www.anthropic.com/engineering/effective-context-engineering-for-ai-agents (accessed October 26, 2026).
  2. 2Anthropic, “Pricing,” Claude Platform Docs, https://platform.claude.com/docs/en/about-claude/pricing (accessed October 26, 2026).

Appendix B · page 6 of 7

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