• (New) Grok 4.6: latest frontier level Grok at only $15 usage
• (New) LongCat-2.0 this is a last gen weak open-weights model
• (Removed) Grok 4.5

LongCat-2.0 is a weak 1.6T-A48B (same size as DeepSeek V4 Pro btw) so it's bewildering why they can serve this one at such generous quota but kneecap DeepSeek V4 Pro.

LLM token economics make no sense, they might as well be stocks at this point

• (New) DeepSeek V4 Flash Vision Exp: new experimental DeepSeek V4 Flash build, adds vision and a small bump in inference as well
• (New) Ox Alpha Free: entirely free and 100% unlimited, only for 1 week though. No one knows what it actually is but it's very capable and multi-modal (equivalent quality to GLM-5.3 and GPT-5.6 Sol)

Model                         5HOURS  1WEEK   1MONTH    CREDITS
-----------------------------------------------------------------
DeepSeek V4 Flash Vision Exp  3800    9450    18900     $15
0x Alpha Free (secret test)   -       -       -         unlimited

0x Alpha is better than DeepSeek V4 Flash 0731 and OpenCode has significantly more capacity for it (100T tokens/day). Sources indicate this model is going to be a surprise when revealed. My guess? a marketing stunt for a new Google or OpenAI model. Reason why I say this is that the model performance is 100% frontier-level and capacity provided is impressive. Whoever is doing this already has a significant infrastructure in-place that's not used much 😅 which excludes most Chinese providers.

New changes in opencode Go plan:

• double DeepSeek V4 Flash usage quota raising it to a $30 credit (from $15)
• add Muse Spark 1.2 Contributor, this model is on par with GPT-5.6 Terra (based on artificial analysis score) and has a very generous quota. However it sends all your data to Meta for collection 🫤

Model                       5HOURS  1WEEK   1MONTH
----------------------------------------------------
Muse Spark 1.2 Contributor  45,300  113,300 226,600
DeepSeek V4 Flash           7,600   18,900  37,800

I was curious about opencode and tried to run it with mistral:7b as well as qwencode3:8b, but it simply couldn't execute a single command.

It was necessary, I think, to be able to execute commands because it kept attempting to write to /home/user. So I told it to run pwd to find out where it was. That always failed.

Was j using a wrong model? Or is opencode just incapable of running commands?

OpenCode Go plan which STILL advertises that it gives users $60/month of credit for each $10/month sub making it one of the best LLM plans out there, is no longer actually doing that. They are now giving users a single pool of $15 of credits for each $10/month sub for all their new models: GLM-5.3, Kimi K3, DeepSeek V4 Pro 0813, and DeepSeek V4 Flash 0731.

This is in spite of new DSV4 and GLM models actually remaining exactly the same as the previous versions but with post-training (same hardware and memory requirements), there's no practical reason for these models to increase prices from both OpenCode and DeepSeek other than sacrificing their goodwill and userbases to increase profit.

This especially applies to DeepSeek V4 Flash as its one of the least demanding on hardware. Some older models still offered by the opencode Go plan at $60 credits require significantly more hardware! (MiMo-V2.5 is a larger model for example)

And the worst part is that opencode still (til this moment) write in their Go FAQ that they offer $60/month credits so this is less than honest on their part:

GLM-5.3 is a post-trained GLM-5.2, still 753B parameters.

Unfortunately, usage cost of GLM-5.3 in Go is currently 4x GLM-5.2, but I expect they'll adjust that once the open weights drop in ~2 weeks:

• 220 requests per 5 hours (880 for GLM-5.2)
• 540 requests per week (2150 for GLM-5.2)

For me, I've set up two additional agents besides Plan and Build:

• Learn: rather than try to implement everything, responds with code snippets and guidelines to implement the feature I want. This speeds up my coding without taking away my agency over the code or building experience. It has become my favorite go-to mode.
• Reviewer: what it says, reviews the code, categorizes its conclusions into: Critical, High, Medium, Low, Polish. Also doesn't modify the code, just provides brief guidelines to resolve the issue.

Pipeline

Generally I start by describing the feature to the Learn agent, it explores the code and creates instructions/guidelines for me to implement it that account for the existing code base expectations and behaviors. I just dive in and implement it.

Then I use the Plan and Build modes to create test suites for the feature as well as implement any trivial code needed.

Once all is clear and ready, I ping the Reviewer to do its thing and usually there are a few false positives, but it does catch real issues. I then implement any necessary fixes and iterate until code is ready.

Model assignments

• Learn: should assign a pro level model with a good linguistic personality. so far I like using: MiMo-V2.5-Pro, Terra-high, DeepSeek V4 Pro
• Plan: should be a frontier-level model. My gotos are: Sol-high and GLM-5.2
• Build: any good coding model. My current gotos are: DeepSeek V4 Flash 0731, Terra-high, Luna-high
• Reviewer: some frontier-level models (like Sol) aren't good for this because they flag way too many "what-if" issues. I prefer: GLM-5.2, Terra-xhigh, DeepSeek V4 Pro

Under the name: DeepSeek V4 Pro (New)

If you can't see it, you probably need to turn on the chinese llm providers toggle in Go's control panel.

DeepSeek V4 Pro 0813 is already available in OpenRouter costing the same as the preview: $0.435 /M tokens input, $0.87 /M tokens output

Published benchmarks puts it way ahead of GLM-5.2, and close to Kimi K3, definitely at frontier level.

As a reminder, Fable 5 costs: $10 /M tokens input, $50 /M tokens output. Making DeepSeek V4 Pro is 20-50x cheaper!

opencode Go is expected to provide access to the new model within 24 hours like they did for previous model releases.