Current as of April 2026. Qwen3.5 397B A17B is a high-reasoning powerhouse with a massive 262K context window, making it a serious contender for long-running Hermes Agent sessions. At $0.39 per million input tokens, it provides a cost-effective way to feed large amounts of persistent memory into your autonomous loops.
Specs
| Provider | Qwen (Alibaba) |
| Input cost | $0.39 / M tokens |
| Output cost | $2.34 / M tokens |
| Context window | 262K tokens |
| Max output | 66K tokens |
| Parameters | N/A |
| Features | function_calling, vision, reasoning |
What it’s good at
Robust Tool Execution
The model handles Hermes’s 47+ built-in tools with high precision, maintaining parameter accuracy even when chaining multiple MCP calls in a single turn.
Massive Context for Memory
The 262K context window allows Hermes to maintain a massive cross-session memory buffer, ensuring the agent doesn’t lose its persona or task history during week-long runs.
Vision-Enabled Reasoning
Native vision support allows the agent to interpret screenshots from desktop environments or messaging platforms when text-based scraping is insufficient.
Where it falls short
Response Latency
Due to its scale, the time-to-first-token is higher than smaller models, which can make real-time platforms like WhatsApp feel sluggish.
Proprietary Constraints
Unlike its open-weight siblings, this variant is proprietary, which might be a dealbreaker for users requiring full local control over their agent’s weights.
Best use cases with Hermes Agent
- Multi-Platform Orchestration — It excels at tracking state across Discord, Slack, and SSH simultaneously without losing the thread of the autonomous objective.
- Complex MCP Tool Chains — The 66K output limit ensures the model can generate long, complex sequences of tool calls and reasoning logs without being truncated.
Not ideal for
- Low-Latency Notification Bots — The overhead of a 397B model is overkill for simple ‘if-this-then-that’ messaging tasks where speed is the priority.
- Strictly Local Deployment — This specific version is hosted and proprietary, making it unsuitable for air-gapped or purely local Hermes setups.
Hermes Agent setup
Configure your provider endpoint to use the qwen/qwen3.5-397b-a17b ID and ensure your timeout settings are increased to accommodate the model’s high reasoning overhead during deep tool-use cycles.
Hermes makes custom endpoints easy. Run:
hermes model
Choose Custom endpoint from the menu. Enter the base URL and model identifier when prompted:
- Base URL:
https://api.haimaker.ai/v1 - Model:
qwen/qwen3.5-397b-a17b
Hermes stores the selection and uses it for all subsequent agent runs across whatever platforms you have wired up (Telegram, Discord, Slack, etc.). Tune HERMES_STREAM_READ_TIMEOUT and related env vars if you’re hitting slow providers.
How it compares
- vs Llama 3.1 405B — Qwen is significantly cheaper at $0.39/$2.34 compared to Llama’s typical $5.00+ pricing on many providers, while offering comparable tool-use reliability.
- vs Claude 3.5 Sonnet — Sonnet is faster for messaging, but Qwen’s 66K output limit is vastly superior for generating long autonomous execution logs that would hit Sonnet’s 8K cap.
Bottom line
A top-tier choice for complex, long-running autonomous agents that need to juggle multiple platforms and massive memory buffers without the premium price tag of western frontier models.
TRY QWEN3.5 397B A17B IN HERMES
For more, see our Hermes local-LLM setup guide.