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Devin for Terminal is a local agent that works with all frontier models, including Opus 4.7, GPT 5.5, and SWE-1.6. You can switch model mid-session, or handoff to Devin in the cloud.

Cognition

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19,795,575 views • 4 months ago •via X (Twitter)

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We rolled out support for GLM 5.3 Flash along with an improved model picker UX in Devin CLI. ⚡ Devin now supports: GLM-5.3, 5.3 Flash, 5.2 Claude Fable, Haiku, Opus, Sonnet GPT-5.6 Sol, Luna, Terra + others DeepSeek V4 Flash, Pro SWE-1.7, 1.6 Gemini 3.7 Flash Grok 4.6, 4.5 Inkling Kimi K3, 2.7 + others Also available in Devin Desktop.

We rolled out support for GLM 5.3 Flash along with an improved model picker UX in Devin CLI. ⚡ Devin now supports: GLM-5.3, 5.3 Flash, 5.2 Claude Fable, Haiku, Opus, Sonnet GPT-5.6 Sol, Luna, Terra + others DeepSeek V4 Flash, Pro SWE-1.7, 1.6 Gemini 3.7 Flash Grok 4.6, 4.5 Inkling Kimi K3, 2.7 + others Also available in Devin Desktop.

nader dabit

89,386 views • 5 days ago

Devin Desktop supports the Agent Client Protocol (ACP): bring your own agents to work alongside Devin, all in one unified view.

Devin Desktop supports the Agent Client Protocol (ACP): bring your own agents to work alongside Devin, all in one unified view.

Cognition

47,627 views • 3 months ago

You don’t have to use one model (or one provider!) for everything. With Workshop, you can combine frontier and local models in the same workflow. For example: Opus can be the main agent, and delegate specific tasks to Gemma 4 via subagents. Better quality where it matters. Better privacy, speed, and cost where it counts. One workflow, best model for each task.

You don’t have to use one model (or one provider!) for everything. With Workshop, you can combine frontier and local models in the same workflow. For example: Opus can be the main agent, and delegate specific tasks to Gemma 4 via subagents. Better quality where it matters. Better privacy, speed, and cost where it counts. One workflow, best model for each task.

Workshop AI

962,487 views • 4 months ago

we compared Gemini 3.1 Pro, Opus 4.7, and GPT 5.5 to Kimi K2.6, Xiaomi Mimo v2.5, and Qwen 3.6 Max in average, closed source are faster. GPT 5.5 and Opus 4.7 the fastest. Kimi K2.6 comes after. It keeps up thanks to its native INT4 quantization. MiMo took the longest, but the refinement and aesthetic only ranks after Gemini 3.1. as if a mini Gemini. Its slow cuz it's trained for long-horizon agentic work. Claude Opus 4.7 is blooming in a very different style, probably because Anthropic trains for taste, not just accuracy.

we compared Gemini 3.1 Pro, Opus 4.7, and GPT 5.5 to Kimi K2.6, Xiaomi Mimo v2.5, and Qwen 3.6 Max in average, closed source are faster. GPT 5.5 and Opus 4.7 the fastest. Kimi K2.6 comes after. It keeps up thanks to its native INT4 quantization. MiMo took the longest, but the refinement and aesthetic only ranks after Gemini 3.1. as if a mini Gemini. Its slow cuz it's trained for long-horizon agentic work. Claude Opus 4.7 is blooming in a very different style, probably because Anthropic trains for taste, not just accuracy.

GMI Cloud

39,221 views • 3 months ago

Qwen 3.7-max beats Opus 4.7 and GPT-5.5 We tested three frontier models on a real agentic task: write a Tetris bot that plays the game and trains itself. Each model could read its own code, run benchmarks, and rewrite itself across 10 iterations. Then we compared the final bots head to head. Qwen 3.7-Max: training cost $1.32, bot improvement +56% Claude Opus 4.7: training cost $12.15, bot improvement +28% GPT-5.5: training cost $2.85, bot improvement +7% Qwen won on every dimension - biggest jump, 9× cheaper than Claude, 2× cheaper than GPT. Long agentic loops is where Qwen Max actually delivers.

Qwen 3.7-max beats Opus 4.7 and GPT-5.5 We tested three frontier models on a real agentic task: write a Tetris bot that plays the game and trains itself. Each model could read its own code, run benchmarks, and rewrite itself across 10 iterations. Then we compared the final bots head to head. Qwen 3.7-Max: training cost $1.32, bot improvement +56% Claude Opus 4.7: training cost $12.15, bot improvement +28% GPT-5.5: training cost $2.85, bot improvement +7% Qwen won on every dimension - biggest jump, 9× cheaper than Claude, 2× cheaper than GPT. Long agentic loops is where Qwen Max actually delivers.

atomic.chat

869,326 views • 3 months ago

You can now connect your OpenRouter URL directly to the Warp Agent. OpenRouter unlocks a world of models including Anthropic, OpenAI, Gemini, DeepSeek, Kimi, and more, all with better prices and uptime. Set your URL, model, and an alias to easily switch using /model.

You can now connect your OpenRouter URL directly to the Warp Agent. OpenRouter unlocks a world of models including Anthropic, OpenAI, Gemini, DeepSeek, Kimi, and more, all with better prices and uptime. Set your URL, model, and an alias to easily switch using /model.

Warp

15,097 views • 3 months ago

Salute to the Qwen team 🫡 We tested Qwen 3.7-Max, Gemini 3.5 Flash, GPT-5.5, and Claude Opus 4.7. The biggest shock came from Qwen. In less than a month (3.6 Max dropped April 20), Qwen went from the worst multimodal output on our sakura tree test, barely keeping up with Gemini, GPT, and Claude , to matching Gemini 3.5 Flash frame for frame on this soccer test, and outperforming GPT-5.5 and Claude Opus 4.7. It rendered a perfectly proportioned soccer player and the most lifelike ball in the entire test. Remarkable spatial reasoning. Also: Gemini 3.5 Flash is now faster than GPT-5.5, which used to be the fastest in our past tests.

Salute to the Qwen team 🫡 We tested Qwen 3.7-Max, Gemini 3.5 Flash, GPT-5.5, and Claude Opus 4.7. The biggest shock came from Qwen. In less than a month (3.6 Max dropped April 20), Qwen went from the worst multimodal output on our sakura tree test, barely keeping up with Gemini, GPT, and Claude , to matching Gemini 3.5 Flash frame for frame on this soccer test, and outperforming GPT-5.5 and Claude Opus 4.7. It rendered a perfectly proportioned soccer player and the most lifelike ball in the entire test. Remarkable spatial reasoning. Also: Gemini 3.5 Flash is now faster than GPT-5.5, which used to be the fastest in our past tests.

GMI Cloud

75,785 views • 3 months ago

You can set up Auto-Triage for any Slack channel with just three clicks. To help get you started, we're offering $200 in credits when you create your first Devin Automation.

You can set up Auto-Triage for any Slack channel with just three clicks. To help get you started, we're offering $200 in credits when you create your first Devin Automation.

Cognition

24,822 views • 3 months ago

My first time building with Opus 4.7 and I love it! I quickly built this Base AI Ecosystem map with names, links logos in the form of a galaxy that you can navigate through 🛰️ With some rigorous prompting, Opus 4.7 did everything for me including descriptions and logos!

My first time building with Opus 4.7 and I love it! I quickly built this Base AI Ecosystem map with names, links logos in the form of a galaxy that you can navigate through 🛰️ With some rigorous prompting, Opus 4.7 did everything for me including descriptions and logos!

Youssef

17,112 views • 4 months ago

Agreed. It's why we've been building a command center in the Warp terminal so you don't need to learn tmux to manage agents. - All conversations are searchable from history - Close tabs and revisit later with session restore - Track both local and cloud agent runs

Agreed. It's why we've been building a command center in the Warp terminal so you don't need to learn tmux to manage agents. - All conversations are searchable from history - Close tabs and revisit later with session restore - Track both local and cloud agent runs

Zach Lloyd

37,857 views • 5 months ago

I don't think there's a single terminal ux that handles agent swarms well With slate, you can literally use Opus 4.6 and GPT 5.4 at the exact same time But making it intuitive took a ton of work So heres a thread on how it works and how to actually use it 🧵

I don't think there's a single terminal ux that handles agent swarms well With slate, you can literally use Opus 4.6 and GPT 5.4 at the exact same time But making it intuitive took a ton of work So heres a thread on how it works and how to actually use it 🧵

akira

139,114 views • 5 months ago

To make it easier to migrate your workflows, we've updated the claude-api skill in Claude Code with Opus 4.7 support. Just say "migrate to Opus 4.7" and it updates model names, prompts, and effort settings for you.

To make it easier to migrate your workflows, we've updated the claude-api skill in Claude Code with Opus 4.7 support. Just say "migrate to Opus 4.7" and it updates model names, prompts, and effort settings for you.

ClaudeDevs

362,429 views • 4 months ago

Open-weight LongCat 2.0 matched GPT-5.5 level on agentic game dev for $0! We ran Meituan's LongCat 2.0 against cloud frontier GPT-5.5 in Kilo CLI with their agent. Same task for both - build a retro Duck Hunt game in one game.html, improved over 3 agent iterations with duck waves, ammo and physics Outputs: LongCat 2.0: 70.3K tokens, $0.00 GPT-5.5: 64.9K tokens, $0.65 LongCat kept up on graphics, physics and game logic. Ducks fly and fall when hit, the dog fetches them, ammo counts down, the waves keep coming. Both ran clean and nothing clipped. The only difference was the bill - GPT cost $0.65, LongCat ran local for $0

Open-weight LongCat 2.0 matched GPT-5.5 level on agentic game dev for $0! We ran Meituan's LongCat 2.0 against cloud frontier GPT-5.5 in Kilo CLI with their agent. Same task for both - build a retro Duck Hunt game in one game.html, improved over 3 agent iterations with duck waves, ammo and physics Outputs: LongCat 2.0: 70.3K tokens, $0.00 GPT-5.5: 64.9K tokens, $0.65 LongCat kept up on graphics, physics and game logic. Ducks fly and fall when hit, the dog fetches them, ammo counts down, the waves keep coming. Both ran clean and nothing clipped. The only difference was the bill - GPT cost $0.65, LongCat ran local for $0

atomic.chat

40,046 views • 1 month ago

We’re shipping Devin Search, a new tool for codebase understanding. Use Devin Search for quick questions like "how is user authentication implemented?" or turn on Deep Mode for complex asks like “draw an architecture diagram explaining our billing system”. 🧵👇

We’re shipping Devin Search, a new tool for codebase understanding. Use Devin Search for quick questions like "how is user authentication implemented?" or turn on Deep Mode for complex asks like “draw an architecture diagram explaining our billing system”. 🧵👇

Cognition

104,840 views • 1 year ago

GPT-5.5 in Codex is built for long-session agent work. But context still doesn't follow you across projects, agents, or teammates. ByteRover does that + Save you tokens -> No rewriting context when you switch from Claude Code to Codex. Now connecting Codex, Claude Code, OpenClaw, Hermes, and 22+ more agents. Your context moves with you. → personal context for solo work → team context for shared decisions and bug history

GPT-5.5 in Codex is built for long-session agent work. But context still doesn't follow you across projects, agents, or teammates. ByteRover does that + Save you tokens -> No rewriting context when you switch from Claude Code to Codex. Now connecting Codex, Claude Code, OpenClaw, Hermes, and 22+ more agents. Your context moves with you. → personal context for solo work → team context for shared decisions and bug history

andy nguyen

12,437 views • 4 months ago

LongCat performed Opus 4.8 and GPT 5.5 level on real physics tasks for $0! We gave 4 models the same prompt: build three self-contained HTML5 canvas scenes with real physics Prompts: - A cannon demolishing a brick wall - A bowling ball knocking down the pins - A tornado that sucks in random objects Outputs: LongCat: 18,015 tokens, $0.00 Opus 4.8: 18,872 tokens, $0.48 GPT 5.5: 32,588 tokens, $0.98 GLM 5.2: 31,062 tokens, $0.09 On the physics LongCat came out ahead of Opus 4.8 and GLM 5.2 - cleaner collisions, nothing clipping or falling through. On detail and rendering it matched GPT 5.5, the best looking of the four. Getting this quality for free is wild!

LongCat performed Opus 4.8 and GPT 5.5 level on real physics tasks for $0! We gave 4 models the same prompt: build three self-contained HTML5 canvas scenes with real physics Prompts: - A cannon demolishing a brick wall - A bowling ball knocking down the pins - A tornado that sucks in random objects Outputs: LongCat: 18,015 tokens, $0.00 Opus 4.8: 18,872 tokens, $0.48 GPT 5.5: 32,588 tokens, $0.98 GLM 5.2: 31,062 tokens, $0.09 On the physics LongCat came out ahead of Opus 4.8 and GLM 5.2 - cleaner collisions, nothing clipping or falling through. On detail and rendering it matched GPT 5.5, the best looking of the four. Getting this quality for free is wild!

atomic.chat

105,523 views • 2 months ago

You can now use GPT 5.5, Gemini 3.7 Flash, Kimi K3 and 47 other AI models completely free😱 No subscription. No credit card. Even the API usage costs $0. AIHubMix just opened a free catalog with 50 AI models. Some of the available models: • Ox Alpha • Gemini 3.7 Flash • GLM 5.2 • Kimi K3 • MiniMax M3 • GPT 5.5 • 40+ more And you don’t need separate API keys for each model. Setup takes 2 minutes: > Step 1: Go to > Create an account using your email or OAuth. No card needed. Step 2: Create one API key > The same key works with every free and paid model. Step 3: Add it to any OpenAI-compatible tool Base URL: Then choose any model ending in -free, such as: coding-glm-5.2-free gpt-5.5-free That’s it. One API key. 50 AI models. $0 for both input and output. Save this. You might need a free multi-model setup later.

You can now use GPT 5.5, Gemini 3.7 Flash, Kimi K3 and 47 other AI models completely free😱 No subscription. No credit card. Even the API usage costs $0. AIHubMix just opened a free catalog with 50 AI models. Some of the available models: • Ox Alpha • Gemini 3.7 Flash • GLM 5.2 • Kimi K3 • MiniMax M3 • GPT 5.5 • 40+ more And you don’t need separate API keys for each model. Setup takes 2 minutes: > Step 1: Go to > Create an account using your email or OAuth. No card needed. Step 2: Create one API key > The same key works with every free and paid model. Step 3: Add it to any OpenAI-compatible tool Base URL: Then choose any model ending in -free, such as: coding-glm-5.2-free gpt-5.5-free That’s it. One API key. 50 AI models. $0 for both input and output. Save this. You might need a free multi-model setup later.

CDG

15,278 views • 12 days ago

MCP is here! You can now give Devin access to your favorite servers via the MCP Marketplace. Think Datadog, Linear, Sentry, Figma, and thousands more. Demos from our team + getting started 👇

MCP is here! You can now give Devin access to your favorite servers via the MCP Marketplace. Think Datadog, Linear, Sentry, Figma, and thousands more. Demos from our team + getting started 👇

Cognition

1,216,011 views • 1 year ago

Funny how you can do the same thing with a local model without sending all your data to a remote cloud.

Funny how you can do the same thing with a local model without sending all your data to a remote cloud.

Victor M

1,196,733 views • 7 months ago

GPT-5.1 is now live in Warp. It’s much faster (40% faster task completion on a subset of SWE-bench Verified) without compromising quality. GPT-5.1 is available to all Warp users, and is now the default model for all new users.

GPT-5.1 is now live in Warp. It’s much faster (40% faster task completion on a subset of SWE-bench Verified) without compromising quality. GPT-5.1 is available to all Warp users, and is now the default model for all new users.

Warp

80,683 views • 9 months ago