Palo Alto
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We've spent the last several months scaling our compute footprint right here in the U.S., and we got to see some of it up close at the @CrusoeAI and Redwood Materials site in Nevada. Thanks @Electron_Cowboy and @ChaseLochmiller for the tour!
Excited to keep building with Crusoe to bring our users day-zero models and full ZDR, with top performance. We look forward to sharing more soon 👀
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San Francisco showed up! 🌉
@ollama's @jmorgan and @TrajectoryLabs' @MichaelElabd joined Crusoe's Erwan Menard to explore a fundamental choice for AI builders: closed, open, or proprietary models?
📸 Moments from an incredible evening. Stay tuned for our next AI talk.
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Clef from @Cloudflare is on Ollama. Run it locally or in the cloud.
27B multimodal decision model, supports text and image input and is compatible with Jev and System One APIs.
🔒Hosted in the US and with zero data retention.
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Ornith 1.5 122B is available on Ollama! Run it all locally on your device.
ollama run ornith-1.5:122b
Aloha!🌺 Meet Ornith-1.5-122B: No Tradeoff Between Strong and Fast
Stronger. Faster. Leaner. Ornith-1.5-122B delivers frontier-level capabilities with exceptional inference efficiency. With superior instruction following, stronger task decomposition, and deeper understanding of real-world workflows, it achieves state-of-the-art performance among open-source models of comparable size, while running on a single NVIDIA DGX card!!
Open weights under the MIT license.
Coding
✅SWE-bench Verified: 0.845
✅TB2.1: 0.813
✅CyberGym: 0.800
✅NL2Repo: 0.512
Agentic
✅HLE: 0.446
✅BrowseComp: 0.785
✅MCP-Atlas: 0.746
✅Toolathlon: 0.708
🤗Hugging Face: huggingface.co/ornith-ai/Orn…
We can’t wait to see what you build with Ornith-1.5-122B.
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For the next 3 days, in collaboration with @MiniMax_AI, MiniMax M3.1 Flash will be free on Ollama's Cloud!
Hosted in the US and with zero data retention.
MiniMax M3.1 Flash is on Ollama!
🔒 Hosted in the US and with zero data retention.
Fast coding and agentic workflows, with image understanding and a 1M-token context window.
Try it on Ollama Cloud:
ollama run minimax-m3.1-flash:cloud
Claude Code:
ollama launch claude --model minimax-m3.1-flash:cloud
Codex:
ollama launch codex -–model minimax-m3.1-flash:cloud
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MiniMax M3.1 Flash is on Ollama!
🔒 Hosted in the US and with zero data retention.
Fast coding and agentic workflows, with image understanding and a 1M-token context window.
Try it on Ollama Cloud:
ollama run minimax-m3.1-flash:cloud
Claude Code:
ollama launch claude --model minimax-m3.1-flash:cloud
Codex:
ollama launch codex -–model minimax-m3.1-flash:cloud
MiniMax M3.1 Flash: Space Performance + Bunny Speed
🚀🐰 Yes, Space Bunny - which has topped global leaderboards with 200T+ tokens - was an earlier version of M3.1 Flash.
💰Redefining the performance economics of agentic AI. M3.1 Flash achieves frontier-level intelligence across key tasks such as Cowork (Automation-Bench: 62%; ALE: 30%), Coding (DeepSWE: 74%) and Visual Reasoning (BabyVision: 91%), at 1/3 the cost of M3 and 3x the speed.
API pricing (flat rate): $0.15 / $0.60 per 1M input/output tokens, with cache reads at $0.015 / 1M tokens.
Model weights will arrive on Oct 23.
API: platform.minimax.io
M Plan: minimax.io/m-plan
MiniMax Code for desktop: agent.minimax.io/download
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✈ DeepSeek-V4.1-Flash-1017 is on Ollama! US-based hosting with zero data retention.
It's strong on agentic tasks while being cheaper per task.
Try it on Ollama Cloud:
ollama run deepseek-v4.1-flash:1017-cloud
Claude Code:
ollama launch claude --model deepseek-v4.1-flash:1017-cloud
OpenCode:
ollama launch opencode --model deepseek-v4.1-flash:1017-cloud
🚀 DeepSeek-V4.1-Flash-1017 is here!
Stronger benchmark performance, faster task completion, and shorter outputs than the previous version—a Pareto improvement in performance and cost. Now live on our website, app, and API.
🛠️ Optimized for @DeepSeekHarness, Tencent CodeBuddy, WorkBuddy, and more. Upgrade to DeepSeek Harness v0.2.1-rc.1 or later for the best experience with the new model.
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Jeffrey Morgan retweeted
.@ollama is now an inference provider on Replicas. Run open models in Claude Code, Codex, OpenCode and Pi
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Working on getting our US hosts up and running. Very soon!
🚀 DeepSeek-V4.1-Flash-1017 is here!
Stronger benchmark performance, faster task completion, and shorter outputs than the previous version—a Pareto improvement in performance and cost. Now live on our website, app, and API.
🛠️ Optimized for @DeepSeekHarness, Tencent CodeBuddy, WorkBuddy, and more. Upgrade to DeepSeek Harness v0.2.1-rc.1 or later for the best experience with the new model.
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Jeffrey Morgan retweeted
In this video, Joseph asks Delta to configure itself to use @ollama as a custom OpenAI-compatible provider. It all happens in the thread, without Joseph ever touching Settings.
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안녕하세요 🇰🇷
Bags packed. Ollama is headed to Seoul ✈️
Korea is one of the most innovative AI markets in the world, and with such an active Ollama community in Seoul, we’ve been wanting to make this trip for a while. We’re really excited to finally go.
This November, we will be in town meeting users, customers and partners, learning how we can further grow in the market.
We’re also teaming up with @friendliai while we’re in Seoul. More on that to follow 👀
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We’re excited to be day 0 partners for @reflection_ai’s first open-weight model! For a limited time,
Beam is FREE on Ollama! In partnership with @reflection_ai this model is hosted in the US with full ZDR.
It has a 1M token context window and is designed for software engineering, reasoning, and long-running agentic tasks.
Run Beam on Ollama’s Cloud:
ollama run beam
Claude Code
ollama launch claude --model beam:cloud
Codex
ollama launch codex --model beam:cloud
OpenCode
ollama launch opencode --model beam:cloud
Free to use for a limited time only.
Beam is now available across platforms, with open weights under the Apache 2.0 license - in collaboration with an ecosystem of 40+ partners.
We're releasing:
- Weights, tokenizer, and reference implementation
- BF16, FP8 and NVFP4 weights and a DFlash2 drafter
- The open source harness we built and trained Beam on: Mirror CLI
Weights and model card on Hugging Face: huggingface.co/reflection
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Want to use @ollama Cloud in a Sprite? We got you.
You can now access Ollama Cloud through our Sprites Connector.
ollama.com/blog/fly-io-sprit…
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Jeffrey Morgan retweeted
Introducing gemma.ai
The new hub for Gemma, including
📚Inference and training guides
🧠 Deep visual architectural guides
🖼️ Online demos, even running models in the browser
And a lot more to come, check it out!
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NVIDIA Nemotron 3.5 Super VL is now available on Ollama
This model combines reasoning and visual understanding across a range of agent workflows.
On a single GPU, this model delivers up to 5x higher throughput for agentic tasks compared to other open models in its size category.
ollama run nemotron-3.5-super
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NVIDIA Nemotron 3.5 Bolt 74B-A9B 24GB is now on Ollama
This model vision-language model (VLM) is designed to run everyday agentic tasks locally, using a native 2-bit quantization to fit in 24GB of memory and run alongside other applications.
ollama run nemotron-3.5-bolt
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Muse Spark Open is now on Ollama.
@Meta's open-weight model for coding and tool use, with a 1M-token context window.
Run it on Ollama’s cloud:
ollama run muse-spark-open:cloud
Use with Claude Code:
ollama launch claude muse-spark-open:cloud
Now available to Max and Teams users, and rolling out to Pro users soon!
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ollama run lfm2.5:24b
ollama.com/library/lfm2.5:24…
Today we release 𝙻𝙵𝙼𝟸.𝟻-𝟸𝟺𝙱-𝙰𝟸𝙱, the largest 𝙻𝙵𝙼𝟸.𝟻 family member. It is an efficient local model for laptops and PCs to work through multi-step tasks inside popular agent harnesses.
> 24B total parameters, 2B active per token
> Context expanded to 131K tokens
> A 128K-token vocabulary
> 33T pretraining tokens
> It is a reasoning model
> Very easy to fine-tune and customize
> Performs competitively with Qwen3.6-35B-A3B, a model with ~50% more total and active parameters, on agentic and tool-use tasks.
> Open base and post-trained weights on @huggingface 🤗
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