# Hermes Index: agentic capability and cost per task inside Hermes Agent (Hermes Index)

> An index of agentic capability from Nous Research. It averages pass@1 scores on four suites, Hermes Bench, TerminalBench 4, TerminalBench Science and SkillsBench, with every run inside the Hermes Agent harness, and reports the mean cost per task beside the score.

Canonical page: https://benchlm.ai/benchmarks/hermesindex

- Category: [Agentic](/agentic)
- Last updated: October 15, 2026 snapshot

Nous Research publishes the Hermes Index as a table of 15 models. Each score is the mean pass@1 result across four suites, Hermes Bench, TerminalBench 4, TerminalBench Science and SkillsBench, with the mean cost per task beside it. We mirror the October 15, 2026 snapshot and keep every suite column.

Every run uses the Hermes Agent harness with reasoning effort set to high where the model offers it. TerminalBench 4 runs without its 4 GPU tasks. Where a SkillsBench run found the suite's public repository, the clean score drops those tasks and is the one that counts; we show the raw score beneath it.

An asterisk marks a provisional figure: a partial run or a cost estimate that Nous says is pending a full rerun. Scores belong to the model and the harness together, so the table is display only.

- [Hermes Index leaderboard](https://portal.nousresearch.com/bench)

## About Hermes Index

- Year: 2026
- Tasks: Four suites: Hermes Bench (150 tasks), TerminalBench 4 without its 4 GPU tasks, TerminalBench Science and SkillsBench
- Format: Mean pass@1 score across four suites, with mean cost per task
- Difficulty: Frontier agentic
- Paper: [Hermes Index: an agentic model leaderboard](https://portal.nousresearch.com/bench)

Nous Research runs each model through Hermes Agent with reasoning effort set to high where the model offers it. The index is the mean of the four suite scores and the mean cost per task across the same suites. Hermes Bench is Nous's own suite; the other three are public benchmarks run in the same harness.

Hermes Index is currently displayed on BenchLM for reference, but it is excluded from the weighted scoring formula.

## Leaderboard (15 models)

| Rank | Model | Hermes Index | Hermes Bench | TerminalBench 4 | TerminalBench Science | SkillsBench (clean / raw) |
|---|---|---|---|---|---|---|
| 1 | [Claude Opus 5.5](/models/claude-opus-5-5) | 63.31 ($4.99*) | 76.7 ($0.516) | 54.0 ($6.27*) | 52.9 ($12.65) | 69.6 ($0.51) |
| 2 | [GPT-6 Astra](/models/gpt-6-astra) | 56.25 ($11.61) | 73.7 ($1.52) | 41.3 ($12.66) | 57.1 ($29.84) | 52.9 ($2.44) |
| 3 | [Claude Sonnet 5.5](/models/claude-sonnet-5-5) | 53.14 ($2.82*) | 73.5 ($0.25) | 36.5 ($2.77*) | 35.7 ($8.02) | 66.9 ($0.23) |
| 4 | [GPT-6 Sol](/models/gpt-6-sol) | 44.10 ($2.23) | 73.5 ($0.263) | 23.8 ($2.53) | 18.6 ($5.7) | 60.5 ($0.42) |
| 5 | [Grok 4.7](/models/grok-4-7) | 39.32 ($10.77) | 74.4 ($0.69) | 12.7 ($23) | 1.4 ($18.41) | 68.8 ($0.99) / 71.9 |
| 6 | [GLM-5.3](/models/glm-5-3) | 39.23 ($3.78) | 71.8 ($0.18) | 38.1 ($7.68) | 1.4 ($6.82) | 45.6 ($0.44) |
| 7 | [Kimi K3](/models/kimi-k3) | 39.16 ($6.5) | 71.5 ($0.176) | 19.0 ($8.57) | 8.6 ($16.74) | 57.5 ($0.53) |
| 8 | [Gemini 3.8 Flash](/models/gemini-3-8-flash) | 38.12 ($3.17) | 62.2 ($0.64) | 23.8 ($5.94) | 8.6 ($5.15) | 57.9 ($0.94) / 67.7 |
| 9 | [DeepSeek V4.1 Flash 1017](/models/deepseek-v4-1-flash) | 36.91 ($0.259) | 70.7 ($0.019) | 17.5 ($0.62) | 2.9 ($0.38) | 56.5 ($0.016) / 61.1 |
| 10 | [Qwen3.8 Max](/models/qwen3-8-max) | 36.17 ($6.69) | 70.5 ($0.322) | 17.5 ($6.84) | 5.7 ($19.09) | 51.0 ($0.52) |
| 11 | [GLM-5.3-Flash](/models/glm-5-3-flash) | 34.95 ($0.497) | 68.9 ($0.019) | 25.4 ($0.6) | 2.9 ($1.31) | 42.6 ($0.058) |
| 12 | [GPT-6 Luna](/models/gpt-6-luna) | 33.89 ($0.141) | 70.5 ($0.015) | 6.3 ($0.24) | 4.8 ($0.28) | 54.0 ($0.03) |
| 13 | [Step 5 Preview](/models/step-5-preview) | 32.83 ($1.75) | 69.2 ($0.17) | 12.7 ($2.63) | 7.1 ($3.84) | 42.3 ($0.35) / 46.6 |
| 14 | [Hy4 preview](/models/hy4-preview) | 26.13 ($0.482) | 58.6 ($0.09) | 12.7 ($0.7) | 1.4 ($0.98) | 31.8 ($0.16) |
| 15 | [Ling 3.0 Flash](/models/ling-3-0-flash) | 21.56 ($0.054) | 53.8 ($0.0036) | 0.0 ($0.08) | 0.0 ($0.12) | 32.4 ($0.013) |

Scores are pass@1 percentages with mean cost per task in USD in parentheses. Every run uses Nous Research's Hermes Agent harness with high reasoning effort where offered. TerminalBench 4 runs without its 4 GPU tasks. An asterisk marks a provisional result pending a full rerun. SkillsBench shows the clean score first and the raw score after the slash.

## FAQ

### What does the Hermes Index measure?

The Hermes Index averages each model's pass@1 score on four agentic suites, Hermes Bench, TerminalBench 4, TerminalBench Science and SkillsBench, all run inside Nous Research's Hermes Agent harness. It also reports the mean cost per task, so you can see what a score costs.

### Which model leads the Hermes Index?

Claude Opus 5.5 leads the October 15, 2026 table with an index of 63.31 at $4.99 per task, a cost Nous marks as provisional. GPT-6 Astra follows at 56.25 and $11.61 per task.

### Why is the Hermes Index display only?

Every score combines the model with the Hermes Agent harness, a fixed reasoning-effort setting, and Nous Research's grading. The harness maker also owns one of the four suites. We show the published table for comparison and keep it out of the weighted model-only ranking.