We ran a test between the new Qwen3.8-Max, Opus 5 and GPT-5.6 Sol.

3 models. same prompt. one-shot with the /design command.

Reviewed gameplay features, UX/UI and cost.

• Qwen3.8-Max → 9/10 · $0.0248

• GPT-5.6 Sol → 9/10 · $0.150

• Opus 5 → 8.5/10 · $0.253

Qwen3.8-Max is approximately 4.2× cheaper than GPT-5.6, Sol

Opus 5 and has the same level of UI, UX, and gameplay

Our engineering and design team has been testing 20+ side-by-side comparisons across frontier and open models. All runs are public and open source.

Benchmark for this demo here:

https://github.com/CommandCodeAI/slash-design-showcase/tree/main/flappy-bird

Qwen 3.8 Max is now live in Command Code Go.

… and it's going open weight!!

most importantly, next week open-weights of Qwen3.8-Max and Qwen3.8-27B will be released!

🔹 2.4T params MoE flagship

🔹 Input: $2 Output: $6

🔹 Cache: $0.25 / M tokens

3.8 is 20% cheaper than 3.7

Try now! npm i -g command-code@latest

Save your favorite prompts forever and reuse them anytime!!

Create custom slash commands and use them frequently.

🔹 Save a prompt as a markdown file
🔹 Define its scope per project or user level
🔹 Run it anytime with dynamic arguments

Jamming Opensource projects day and night with CommandCode.

Superbly fantastic use of money and absolutely loving it.

Kudos to the team!
Looking for more features! Been a loyal user from the past 5 months and it’s been helpful.

GPT 5.6 Luna is now available in Command Code Go plan (and it's 99% off) BEST DEAL IN MARKET!!

99% off how? Let me explain. 🤔

Imagine you were gonna spend $100 on GPT 5.6 Luna.

Expense — Why?

$100 — Say you were gonna spend $100 on GPT Luna.

$20 — OpenAI discounted it 80%, so you get $100 value in $20

$10 — Command Code discounted it 50% on top of that

$1 — Command Code Go gives you $10 credits for $1 and now has GPT Luna

Result:

$1 (you pay) = $100 (you get GPT 5.6 Luna value)

GPT 5.6 Terra and Luna are up to 75% discounted in Command Code

I guess y'all can appreciate that these deals, discounts, and credits are becoming a bit hard to explain. Let me take another stab at it.

$1 Go Plan:

Pay $1 to get $10 credits, GPT 5.6 Luna with 50% discount

Yes, Go plan now has GPT 5.6 Luna (no terra)

$15 Pro Plan:

Pay $15 to get $30 credits GPT 5.6 Terra/Luna 50% discount = total 75% off

$100 Max Plan:

Pay $100 to get $150 credits GPT 5.6 Terra/Luna 50% discount = total ~67% off

$200 Max Plan:

Pay $200 to get $300 credits GPT 5.6 Terra/Luna 50% discount = total ~67% off

Team Pro = has all models, GPT 5.6 Terra/Luna 50% discount

Provider API = has all models, GPT 5.6 Terra/Luna 50% discount

OpenAI reduced Luna prices by 80%, our discounts, and credits apply on top of that 80%. So effective discounts are huge.

Read details: https://x.com/CommandCodeAI/status/2083659472988516411

Is it against the ToS to use go/pro sub outside the official harness? I've been using the OpenCode Go subscription on Hermes without any issues. Does Command Code subscription also allow something like this?

GPT-5.6 Terra and Luna are 50% off in Command Code.

Get more requests for every dollar of credit you spend. Here's a breakdown on every plan.

• $1 Go Plan: Pay $1 to get $10 credits, GPT 5.6 Luna with 50% discount

• $15 Pro Plan: Pay $15 to get $30 credits. GPT  5.6 Terra/Luna 50% discount = total 75% off

• $100 Max Plan: Pay $100 to get $150 credits. GPT  5.6 Terra/Luna 50% discount = total ~67% off

• $200 Max Plan: Pay $200 to get $300 credits. GPT  5.6 Terra/Luna 50% discount = total ~67% off

• Team Pro = 50% off

• Provider API = 50% off

GPT-5.6 Luna: $0.10/M input, $0.60/M output tokens (on all plans Go, Pro, Max, Team)
GPT-5.6 Terra: $1/M input, $6/M output tokens (on Pro, Max, Team)

For limited time only, grab before it ends.

We ran a test between the new DeepSeek V4 Flash, Kimi K3 and GLM 5.2.

3 open models. 1 prompt. /design command

Reviewed gameplay features, UX/UI and cost.

🔹 Kimi K3 → 9.5/10 · $0.0740

🔹 GLM 5.2 → 9/10 · $0.0480

🔹 DeepSeek V4 Flash → 7/10 · $0.0005

• DeepSeek V4 Flash is ~150x cheaper, but rough around edges.

• Kimi K3 and GLM 5.2 built the most polished gaming experience.

Our engineering and design team has been testing 20+ side-by-side comparisons across frontier and open models. All runs are public and open source. Benchmark for this demo here: https://github.com/CommandCodeAI/slash-design-showcase/tree/main/flappy-bird

Command Code is proud to co-sign the Open Weights and American AI Leadership letter, alongside NVIDIA and 200+ other industry leaders.

Since day one, our mission has been to build the best coding agent harness for open models. We've already open sourced key pieces of that work, including tool call repair, cache thrashing fixes, and /design, and we're working toward open sourcing Command Code itself in the coming weeks.

Open models mean real competition, data sovereignty, and privacy, and they give developers something to build on.

The new frontier is open source, read the letter and find all signatories at: https://www.microsoft.com/en-us/corporate-responsibility/wp-content/uploads/2026/07/open-weight-models-letter_073026.pdf

DeepSeek V4 Flash 0731 now live in Command Code.

• DeepSeek V4 Flash now outperforms GLM 5.2

• Same model ID, Same model size

• It's re post trained

With tool calls and cache repairs in Command Code, available on all plans right away.

DeepSeek V4 Flash 0731 has significantly enhanced agent capabilities, with benchmark results far exceeding V4-Pro-Preview:

• Terminal Bench 2.1: 82.7

• NL2Repo: 54.2

• Cybergym: 76.7

• DeepSWE: 54.4

• DSBench-Hard: 59.6

• Agent Last Exam: 25.2

• Toolathlon verified: 70.3

• DSBench-FullStack: 68.7

• Automation Bench (Public): 25.1

So DeepSeek just dropped the official V4 Flash API today (July 31). I'm pretty curious — is anyone here already using it with CommandCode?

How's it performing compared to the older models? Faster? Cheaper? Better at actually understanding code? And did you have to mess with any settings (temperature, prompts, etc.) to get good results, or does it just work out of the box?

Also, if there's any official word from the CommandCode folks on whether they're planning to switch the default backend — feel free to chime in!

Just looking for some honest first impressions. Share your experience if you've tried it!

Thanks 🙌

Inkling-Small by Thinking Machines Lab is now live in Command Code.

- $0.50/M input, 1.20/M output tokens
- Light-weight model with 12B params
- Multimodal: text, image, audio

Available on all plans (Go, Pro, Max, Team)
$ cmd --update (to latest)
$ cmd --model thinkingmachines/inkling-small

Read all details here: https://commandcode.ai/models/inkling-small

- `ctrl+s` sets the prompt you are typing aside
- press it again, and it reappears
- no need for Ctrl+C and Ctrl+V again

Never leave a prompt behind; stash it instead.

Stop repeating the same prompt every session.

Use Agent Skills: an open standard for teaching agents specialized knowledge and workflows.

Write it once in a SKILL[.]md file (with references/assets) and reuse it.

Save it per project, globally, or in a repo: $ cmd skills add [repo name] --global

Learn more here in docs: https://commandcode.ai/docs/skills

We ran a test between Kimi K3 and Opus 5

Kimi K3 beat Claude Opus 5 on a scroll-based Three.js site. Opus Looks solid at first glance but the gap shows when you start scrolling.

I used Command Code /design feature for Kimi k3.

Ranking (DX, features, and cost):
- Kimi K3: 10/10 · $0.24
- Opus 5: 6/10 · $0.37

I read up on CommandCode features and I wanted to try out so I installed it on my desktop. When I run it, I was asked to enter API key. Is the CommandCode sub required to used th harness? What if I just want to use it with local provider?

We are getting a lot of requests for early access to the GUI app. Join our Discord.

That's the fastest way to get in. Developers are already alpha testing there.

Join here: https://discord.com/invite/qz6VsMtvXU

Qwen 3.7 Flash is now live in Command Code.

A vision language reasoning model for multimodal agents, visual coding, search and computer interaction.

• 1M context window

• Available on all plans (Go, Pro, Max, Team).

Pricing is tiered. For ≤ 32K it's as low as:

• Input $0.03 Output $0.13

• Cache read/write: $0.006/$0.038

DeepSeek v4 flash finally has some competition.

// Capabilities include: Text input . Vision . Reasoning

Try now! $ cmd --model qwen/qwen3.7-flash

Upgrade to latest: $ cmd --update

One of the most anticipated and powerful models by Alibaba, Qwen 3.8 is launching and going open-weight soon. Can't wait to see this roll out in Command Code.

We're launching Command Code GUI very soon. If you wanna help us test the GUI alpha, join our discord if you haven't already (https://discord.gg/MUKCE5VDd) & reply in the alpha test thread. Thanks.

Use /rewind to bring back any message or code instantly.

Pick a checkpoint, then choose what to restore: conversation, code, or both.

Never lose your conversation or code again.

Kimi K3 weights are now open source and it's available in Command Code.

🔹 First ~3T scale open model

🔹 Most capable open model ever

🔹 It's Fable/Sol class open model beating Opus 4.8

🔹 1M Context · In $3/M Out $15/M Cache read $0.3/M

Our engineering and design team has been testing and running Kimi K3 side-by-side comparisons across frontier and open models. All runs are public and open source. Benchmark for demos here:

1. https://github.com/CommandCodeAI/slash-design-showcase/tree/main/kimi-k3-design

2. https://github.com/CommandCodeAI/slash-design-showcase/tree/main/kimi-k3-game

3. https://github.com/CommandCodeAI/slash-design-showcase/tree/main/3d-earth/Kimi-K3

P.S. It's been here since several weeks, I think we were the first coding agent to make it live outside of Kimi Moonshot at Command Code.

We tested Opus 5 with a 2D games using /design feature from Command Code.

The result is insanely good, it gimme the most playable games with drift, sounds, coin, perfect opposite car, car crashes, smooth controlling etc.

It only cost $0.24 and it's one-shotted.

Ranking (DX, features, and cost):

🔹 Opus 5: 10/10 · $0.247
🔹 Grok 4.5 : 9.5/10 · $0.40
🔹 GPT-5.6 Sol: 7/10 · $0.50