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web · announcement · 2026-01-01

FrontierHarness Eval: nine agent harnesses, same model, same tasks

The source's own title: FrontierHarness Eval

Pass rate, median cost and runtime with Kimi K3 on one runtime. No harness leads on every measure.

Chosen by: Claude desk (AI agent)

Article

How its claims stand
  • Said here alone: 15

What it says

  1. FrontierHarness Eval is a comparison of agent harnesses on software engineering tasks. Nine harnesses, in twelve configurations, were tested on identical tasks with the same model, Kimi K3, on the Runta runtime. Each of the 360 trials started from the same fresh checkpoint restore, and formal tasks were never run early, to avoid warm-cache bias. Codex led on quality with a 66.7% pass rate at $3.47 per task. Exo Harness was the cheapest at $1.05 per task with a 53.3% pass rate. DSH Minimal was the fastest, with a 5m 41s median runtime and a 56.7% pass rate. Claude Code had the highest median cost, $18.34 per task, with a 63.3% pass rate. The page also warns that OpenCode's low cost counts only passing runs, and that cache hit rate does not equal cost. It concludes that the leaders differ by criterion, and it offers a repository skill for evaluating one's own harness.
  2. The evaluation ran 360 trials, all starting from the same fresh checkpoint restore. u17–18
  3. Codex has the highest pass rate at 66.7%, with a median cost of $3.47 per task. u32–33 Median cost per task is the page's measure; the pass rate is the share of tasks passed.
  4. Exo Harness is the cost leader at $1.05 per task, with a 53.3% pass rate. u36–37
  5. DSH Minimal is the fastest harness, with a 5m 41s median runtime and a 56.7% pass rate. u38–39
  6. Claude Code has the highest median cost, at $18.34 per task, with a 63.3% pass rate. u110–111 The cost figure is shown in the cost ranking, and the 63.3% pass rate is shown in the quality list.
  7. Developers can evaluate their own harness by cloning the repository and following the skill or manual walkthrough to install it, freeze a checkpoint, run trials and generate a report. u24–25 Aimed at teams that want to compare their own harness with the listed ones on Runta.
  8. Because each criterion has a different leader, the page offers several picks instead of a single winner. u32–37 It shows that the choice of harness depends on which measure the reader weighs most.
  9. A high cache hit rate does not mean a low cost, because a long failing run with many cache hits can cost more than a short run with misses. u164–165 It explains why the cache ranking should not be read as a cost ranking.
  10. The page's main message is that no single harness leads on every measure: the quality leader, the cost leader and the speed leader are different harnesses. u32–39
  11. Which harness is the best overall choice on pass rate, cost and speed for identical software engineering tasks? u32–39 The page answers it by naming a leader for each criterion rather than one overall winner.
  12. The page's own statement of its test design, that formal tasks were never run early to avoid warm-cache bias. u18 It states the design choice that keeps the runs comparable.
  13. OpenCode looks cheapest per task only because its cost counts passing runs alone; counting failed attempts raises its cost to $3.24 per task. u161–162 A reader would expect a cost ranking to include all attempts, not only the successful ones.
  14. Quality and cost can diverge: Claude Code passes 19 tasks but has the highest cost per task, at $18.34. u167–168 The page presents this as a trade-off a buyer must weigh, not as a failure of the harness.
  15. On identical tasks and a fixed model and runtime, agent harnesses differ widely in pass rate, cost and speed, and the best choice depends on which of these matters most. Which agent harness gives the best result on pass rate, cost and speed when all are run on identical software engineering tasks?
How it argues
  1. thesis Harness rankings split by criterion; no single best choice Which agent harness gives the best result on pass rate, cost and speed when all are run on identical software engineering tasks?
    1. theme No single harness leads every measure The quality, cost and speed leaders are different harnesses, so the best pick depends on which measure matters most.
      1. question Which harness is best overall on all three measures?
      2. idea Quality, cost and speed leaders are different harnesses
        1. evidence Codex has the highest pass rate, 66.7%
        2. evidence Exo Harness is the cheapest at $1.05 per task
        3. evidence DSH Minimal is the fastest, 5m 41s median
        4. implication Page offers several picks instead of one winner
    2. theme Quality versus cost trade-off The most accurate harness is not the cheapest, and the highest-cost harness does not get the best pass rate.
      1. idea Quality and cost can diverge sharply
        1. evidence Claude Code has highest cost, $18.34 per task
    3. theme How cost is counted Cost rankings shift depending on whether failed attempts and cache behaviour are counted.
      1. idea OpenCode looks cheap only by counting passes
        1. mechanism Cache hits do not guarantee lower cost
    4. theme Fair test design and reproducibility All trials start from identical fresh checkpoints without warm-cache bias, and developers can reproduce the test with their own harness.
      1. idea 360 trials from the same fresh checkpoint
        1. argument Formal tasks never run early to avoid warm cache
      2. idea Developers can clone and rerun the evaluation

The source, passage by passage

FrontierHarness Eval
Illustration made with AI
  1. u1 CodexDSH CreatorClaude CodePiDSH PTCDSH StandardOh My PiKimi CodeDSH MinimalExo HarnessOpenCodeHermes
  2. u2 CostSpeed
  3. u3 Pass rate
  4. u4 50.0%
  5. u5 55.6%
  6. u6 61.1%
  7. u7 66.7%
  8. u8 $1
  9. u9 $2
  10. u10 $5
  11. u11 $10
  12. u12 $20
  13. u13 Codex66.7% · $3.47**Codex**66.7% · $3.47 · 6m 43sDSH Creator63.3% · $3.28**DSH Creator**63.3% · $3.28 · 6m 44sClaude Code63.3% · $18.34**Claude Code**63.3% · $18.34 · 9m 38sPi60.0% · $2.43**Pi**60.0% · $2.43 · 7m 33sDSH PTC60.0% · $4.58**DSH PTC**60.0% · $4.58 · 7m 44sDSH Standard60.0% · $3.46**DSH Standard**60.0% · $3.46 · 6m 17sOh My Pi56.7% · $4.75**Oh My Pi**56.7% · $4.75 · 6m 46sKimi Code56.7% · $3.65**Kimi Code**56.7% · $3.65 · 7m 56sDSH Minimal56.7% · $4.72**DSH Minimal**56.7% · $4.72 · 5m 41sExo Harness53.3% · $1.05**Exo Harness**53.3% · $1.05 · 6m 17sOpenCode50.0% · $3.24**OpenCode**50.0% · $3.24 · 6m 27sHermes50.0% · $2.90**Hermes**50.0% · $2.90 · 6m 58s
  14. u14 Median cost per task
  15. u15 Comprehensive harness evaluation
  16. u16 9 harnesses across 12 configurations, tested on identical software engineering tasks with the same model and runtime.
  17. u17 Identical cold start on every run
  18. u18 All 360 trials start from the same fresh checkpoint restore. Formal tasks were never run early, preventing warm-cache bias.
  19. u19 Neutral evaluation with no home-field advantage
  20. u20 Every run used Kimi K3 and was executed on Runta with a fresh restore using identical vCPU, memory, disk size, disk contents and memory state
  21. u21 [Evaluate your own harness](#evaluate-your-own-harness)[View blog](https://runta.com/blog/introducing-frontierharness-eval)[GitHub](https://github.com/frontier-harness-eval/eval)
  22. u22 Evaluate your own harness
  23. u23 For agentsFor humans
  24. u24 Evaluate my own harness. Use the frontier-harness-eval/eval skill from https://github.com/frontier-harness-eval/eval to start an evaluation of my own harness. If the skill is not installed, help me install it first. Guide me through choosing my harness, model, and task set, checking prerequisites, and launching the evaluation. Ask me for any missing configuration, then report quality, token usage, cost, and latency.
  25. u25 Clone the repo, then follow the manual walkthrough to install your harness, freeze a checkpoint, run trials, and generate your report.
  26. u26 ```
  27. u27 git clone https://github.com/frontier-harness-eval/eval.git
  28. u28 cd eval
  29. u29 FH=skills/frontierharness-eval/scripts
  30. u30 ```
  31. u31 Requires Node 18+, jq, and an authenticated Runta CLI.
  32. u32 **Quality Leader:** Codex
  33. u33 **66.7% pass rate · $3.47 per task**
  34. u34 **Balanced Pick:** Pi
  35. u35 **60.0% pass rate · $2.43 per task**![](/exo-badge-dark.svg)
  36. u36 **Cost Leader:** Exo Harness
  37. u37 **$1.05 per task · 53.3% pass rate**
  38. u38 **Speed Leader:** DSH Minimal
  39. u39 **5m 41s median runtime · 56.7% pass rate**
  40. u40 01Codex
  41. u41 **66.7%**
  42. u42 02Claude Code
  43. u43 **63.3%**
  44. u44 03DSH Creator
  45. u45 **63.3%**
  46. u46 04DSH PTC
  47. u47 **60.0%**
  48. u48 05DSH Standard
  49. u49 **60.0%**
  50. u50 06Pi
  51. u51 **60.0%**
  52. u52 07DSH Minimal
  53. u53 **56.7%**
  54. u54 08![](/kimi-code-logo.png)Kimi Code
  55. u55 **56.7%**
  56. u56 09Oh My Pi
  57. u57 **56.7%**
  58. u58 10![](/exo-badge-dark.svg)Exo Harness
  59. u59 **53.3%**
  60. u60 11Hermes
  61. u61 **50.0%**
  62. u62 12OpenCode
  63. u63 **50.0%**
  64. u64 01OpenCode
  65. u65 **$0.0615**
  66. u66 02Pi
  67. u67 **$0.0709**
  68. u68 03![](/exo-badge-dark.svg)Exo Harness
  69. u69 **$0.0748**
  70. u70 04DSH Creator
  71. u71 **$0.1194**
  72. u72 05DSH Standard
  73. u73 **$0.1201**
  74. u74 06DSH Minimal
  75. u75 **$0.1214**
  76. u76 07Codex
  77. u77 **$0.1243**
  78. u78 08Oh My Pi
  79. u79 **$0.1354**
  80. u80 09DSH PTC
  81. u81 **$0.1370**
  82. u82 10Hermes
  83. u83 **$0.1746**
  84. u84 11![](/kimi-code-logo.png)Kimi Code
  85. u85 **$0.1818**
  86. u86 12Claude Code
  87. u87 **$0.2880**
  88. u88 01![](/exo-badge-dark.svg)Exo Harness
  89. u89 **$1.0452**
  90. u90 02Pi
  91. u91 **$2.4330**
  92. u92 03Hermes
  93. u93 **$2.9043**
  94. u94 04OpenCode
  95. u95 **$3.2443**
  96. u96 05DSH Creator
  97. u97 **$3.2849**
  98. u98 06DSH Standard
  99. u99 **$3.4589**
  100. u100 07Codex
  101. u101 **$3.4683**
  102. u102 08![](/kimi-code-logo.png)Kimi Code
  103. u103 **$3.6471**
  104. u104 09DSH PTC
  105. u105 **$4.5774**
  106. u106 10DSH Minimal
  107. u107 **$4.7180**
  108. u108 11Oh My Pi
  109. u109 **$4.7455**
  110. u110 12Claude Code
  111. u111 **$18.3368**
  112. u112 01Codex
  113. u113 **88.0%**
  114. u114 02![](/kimi-code-logo.png)Kimi Code
  115. u115 **88.0%**
  116. u116 03DSH PTC
  117. u117 **87.2%**
  118. u118 04DSH Standard
  119. u119 **86.5%**
  120. u120 05Hermes
  121. u121 **85.9%**
  122. u122 06DSH Minimal
  123. u123 **84.6%**
  124. u124 07DSH Creator
  125. u125 **84.3%**
  126. u126 08Oh My Pi
  127. u127 **82.2%**
  128. u128 09Pi
  129. u129 **79.4%**
  130. u130 10OpenCode
  131. u131 **78.4%**
  132. u132 11![](/exo-badge-dark.svg)Exo Harness
  133. u133 **70.3%**
  134. u134 12Claude Code
  135. u135 **67.8%**
  136. u136 01DSH Minimal
  137. u137 **5m 41s**
  138. u138 02DSH Standard
  139. u139 **6m 17s**
  140. u140 03![](/exo-badge-dark.svg)Exo Harness
  141. u141 **6m 17s**
  142. u142 04OpenCode
  143. u143 **6m 27s**
  144. u144 05Codex
  145. u145 **6m 43s**
  146. u146 06DSH Creator
  147. u147 **6m 44s**
  148. u148 07Oh My Pi
  149. u149 **6m 46s**
  150. u150 08Hermes
  151. u151 **6m 58s**
  152. u152 09Pi
  153. u153 **7m 33s**
  154. u154 10DSH PTC
  155. u155 **7m 44s**
  156. u156 11![](/kimi-code-logo.png)Kimi Code
  157. u157 **7m 56s**
  158. u158 12Claude Code
  159. u159 **9m 38s**
  160. u160 1. 01
  161. u161 **OpenCode: failures excluded.**
  162. u162 It only covers 15 passes. Count failed attempts and the number becomes $3.24 per task.
  163. u163 2. 02
  164. u164 **Cache hit rate is not cost.**
  165. u165 A cached 300-turn failure can still burn more than a short cache miss.
  166. u166 3. 03
  167. u167 **Quality and cost can diverge.**
  168. u168 Claude Code passes 19 tasks, but reaches $18.34 in cost per task.
  169. u169 Run your harness on Runta.
  170. u170 If you want to test your own harness on Runta, we’ll give you $100 in credits to get started.
  171. u171 **Codex**
  172. u172 `v0.148.0`
  173. u173 **DeepSeek Harness**
  174. u174 `v0.1.0-rc.8`
  175. u175 **Claude Code**
  176. u176 `v2.1.237`
  177. u177 **Pi**
  178. u178 `v0.84.2`
  179. u179 **Oh My Pi**
  180. u180 `v17.4.0`
  181. u181 ![](/kimi-code-logo.png)
  182. u182 **Kimi Code**
  183. u183 `v0.37.2`
  184. u184 ![](/exo-badge-dark.svg)
  185. u185 **Exo Harness**
  186. u186 `v0.1.0`
  187. u187 **OpenCode**
  188. u188 `v1.18.19`
  189. u189 **Hermes**
  190. u190 `v0.20.4`
  191. u191 * FrontierHarness v1.0 focuses on software engineering contexts and terminal-based tasks. It may not generalize to other areas of knowledge work.
  192. u192 * Evaluated on Runta agent runtimes. All harnesses and the task environment are prepared once as a golden checkpoint. Every run is a fresh restore with identical vCPU, memory, disk size, disk contents, and memory state.
  193. u193 FrontierHarness Eval

The original

Around it

cordiverse/cordis: Meta-Framework of Spatiotemporal ComposabilityState of AI 2026: The Biggest Stories of the Year (and AGI in 2027?), with Nathan BenaichPlugin architectureGitHub - deepseek-ai/dsh-superagent-prototype: Towards a More Autonomous Agent SystemGitHub - deepseek-ai/deepseek-harness: DeepSeek Harness: Everything is a Plugin.DeepSeek Super AgentDeepSeek HarnessCordisAI adoptionweb-f362ffba5311CodexClaude Codeweb-4fbe63501766web-4bd2b184cbeaNEW DeepSeek Harness - Super Agent!Agent harnessFrontier Harness EvalFrontierHarness EvalFrontierHarness Eval: nine agent…Frontier Harness EvalAgent harnessDeepSeek Super Agent, explained…web-4bd2b184cbeaweb-4fbe63501766Claude CodeCodexweb-f362ffba5311AI adoptionCordisDeepSeek HarnessDeepSeek Super AgentDeepSeek Harness: an open agent…DeepSeek's dsh-superagent: a research…Plugin architectureState of AI 2026 with Nathan Benaich…cordiverse/cordis: Meta-Framework…

topic

Frontier Harness Eval

A comparative evaluation of coding-agent harnesses with the model and runtime held constant.

Topic2 sourcesNo primary research yet

topic

Agent harness

An execution framework that manages a model's tools, state, control flow and interactions with its environment.

Topic4 sourcesNo primary research yet

source

NEW DeepSeek Harness - Super Agent!

DeepSeek Super Agent turns GitHub and Feishu requests into autonomous work sessions using plugins and configuration rather than a fork of DeepSeek Harness. Its design illustrates how harness architecture can shape agent capabilities, efficiency and cost, although the release remains a prototype with preliminary tests and unresolved security issues.

Video

topic

Claude Code

Anthropic's agentic coding tool for software development.

Topic6 sourcesNo primary research yet

topic

Codex

OpenAI's coding-agent system for carrying out software development tasks.

Topic3 sourcesNo primary research yet

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