Current as of April 2026. Qwen3.5-35B-A3B is a mid-tier powerhouse optimized for long-context tool orchestration within Hermes. At $0.16 per million input tokens, it provides a massive 262K context window that is essential for maintaining persistent memory across weeks of messaging history.
Specs
| Provider | Qwen (Alibaba) |
| Input cost | $0.16 / M tokens |
| Output cost | $1.30 / M tokens |
| Context window | 262K tokens |
| Max output | 66K tokens |
| Parameters | N/A |
| Features | function_calling, vision, reasoning |
What it’s good at
Massive Context Retention
The 262K context window allows Hermes to recall specific details from deep in a Discord or Slack history without losing its persistent identity.
Superior Tool Orchestration
It handles the 47+ built-in Hermes tools and complex MCP protocols with higher reliability than most models in the 30B-40B parameter range.
Multilingual Reasoning
If your agent monitors global channels, Qwen’s ability to reason across CJK and European languages ensures cross-platform automation stays accurate.
Where it falls short
Reasoning Latency
The internal reasoning overhead can cause noticeable delays when Hermes needs to provide instant responses to fast-moving messaging threads.
Output Cost Ratio
At $1.3 per million output tokens, the cost is nearly 8x the input price, which adds up quickly if your agent generates long summaries or frequent status updates.
Best use cases with Hermes Agent
- Cross-Platform Context Sync — The 262K context window is perfect for agents that need to monitor Slack, run shell commands, and post updates to Telegram based on long-term project history.
- Vision-Integrated Automation — Hermes can use this model’s vision features to analyze screenshots or charts shared in messaging apps to trigger specific MCP tool sequences.
Not ideal for
- Sub-Second Chat Responses — The reasoning steps introduce lag that makes it feel sluggish for basic 1-on-1 WhatsApp or Telegram chats.
- Strictly Local Deployments — This specific proprietary variant is designed for hosted API use, making it difficult to run on consumer-grade Mac hardware compared to standard open-weight versions.
Hermes Agent setup
Configure your provider to allow the full 262K context limit to prevent Hermes from losing its closed-loop learning data during long autonomous runs.
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/qwen3.5-35b-a3b
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-3.1-70B — Llama is more robust for general logic, but Qwen’s 262K context window destroys Llama’s standard limits for long-term agent memory.
- vs Mistral Small — Mistral is faster and cheaper for simple tasks, but Qwen3.5-35B-A3B is far more reliable for complex, multi-step tool calls and MCP handling.
Bottom line
Qwen3.5-35B-A3B is the best choice for Hermes users who need massive context and reliable tool-use for complex automations without the premium price of 400B+ models.
For more, see our Hermes local-LLM setup guide.