TheDrummer: Artemis v1.1
Artemis v1.1 is a reasoning model from TheDrummer released on Sep 6, 2026. It reads text and images and writes text, with a 262K token context window and up to 33K tokens per reply.
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It costs $0.10 per million input tokens and $0.45 per million output tokens. Cached input bills at $0.05, 50% less than fresh input.
It supports tool calling and prompt caching, and its weights are open, so you can host it yourself.
- Modalities
- In / out price
- $0.10 / $0.45 per 1M
- Context
- 262K
- Max output
- 33K
- Released
- Sep 6, 2026
- Knowledge cutoff
- n/a
- Tool calling
- Structured output
- Reasoning
- Prompt caching
- Open weights
- Free to use
Artemis v1.1 pricing
USD, as listed on Oct 15, 2026. Most bills are input heavy, so the cached input rate matters as much as the headline price.
| Input | $0.10 / 1M tokens | |
|---|---|---|
| Output | $0.45 / 1M tokens | |
| Cached input (read) | $0.05 / 1M tokens | 50% off input |
What Artemis v1.1 costs per month
Pick a workload close to yours or type your own volumes.
Supported request parameters
What you can set when you call Artemis v1.1 through an OpenAI compatible API.
- Tools
tools - Reasoning
reasoning
Alternatives to Artemis v1.1
Models that take the same inputs and call tools, closest in price, cheaper ones first.
- Index 37.9
Reads text, images, audio and video. Tool calling, structured output, reasoning. Served by 17 providers.
by xiaomiSep 22, 20261.05M context$0.14/M input tokens$0.28/M output tokens17 providers
- 1.05M context
Reads text, images, files, audio and video. Tool calling, structured output, reasoning. Served by 23 providers.
by googleJun 17, 2025$0.10/M input tokens$0.40/M output tokens23 providers
- 262K context
Reads text and images. Tool calling, structured output, reasoning. Served by 2 providers.
by prism-mlSep 18, 2026$0.075/M input tokens$0.50/M output tokens2 providers
- 262K context
Reads text and images. Tool calling, structured output, reasoning. Served by 2 providers.
by bytedanceApr 28, 2026$0.10/M input tokens$0.40/M output tokens2 providers
- 1.05M context
Reads text, images, audio and video. Tool calling, structured output, reasoning. Served by 21 providers.
by xiaomiApr 22, 2026$0.14/M input tokens$0.28/M output tokens21 providers
- 256K context
Reads text and images. Tool calling, structured output, reasoning. Served by 8 providers.
by bytedance-seedFeb 14, 2026$0.10/M input tokens$0.40/M output tokens8 providers
More from TheDrummer
- 131K context
Reads text.
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- 33K context
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by thedrummerDec 25, 2025$0.1003/M input tokens$0.1207/M output tokens
- 131K context
Reads text. Tool calling, structured output. Served by 3 providers.
by thedrummerSep 27, 2025$0.35/M input tokens$0.55/M output tokens3 providers
- 33K context
Reads text.
by thedrummerJul 22, 2025$0.2006/M input tokens$0.2414/M output tokens
- 33K context
Reads text and files. Structured output. Served by 3 providers.
by thedrummerMar 10, 2025$0.55/M input tokens$0.80/M output tokens3 providers
- 33K context
Reads text.
by thedrummerFeb 17, 2025$0.1003/M input tokens$0.1207/M output tokens
Artemis v1.1 questions
How much does the Artemis v1.1 API cost?
$0.10 per million input tokens and $0.45 per million output tokens, with cached input at $0.05. The estimator on this page turns that into a monthly bill for your own workload.
What is the context window of Artemis v1.1?
262,144 tokens of input, and it can write up to 32,768 tokens in one reply. As a rough guide, a million tokens is around 750,000 English words.
Does Artemis v1.1 support tool calling?
Yes. It accepts tool definitions, which is what an agent needs to call your APIs.
Is Artemis v1.1 open source?
Its weights are published, so you can run it on your own hardware or a cloud of your choice. Read the license before commercial use.
When was Artemis v1.1 released?
Sep 6, 2026.
Catalog data from models.dev (MIT licensed), refreshed daily, last on Oct 15, 2026. The summary is written from these facts.
Building on Artemis v1.1?
I test your real tasks on it and the two closest alternatives, then ship the agent on whichever wins on cost and accuracy.
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