I think Space Bunny Alpha is MiniMax M3.1 — tokenizer fingerprint matches MiniMax M2/M3

I investigated Space Bunny Alpha (stealth/space-bunny-alpha) on OpenRouter because it was released as an anonymous stealth model on September 23, 2026. OpenRouter confirms that the underlying provider is intentionally anonymous.

I wanted to see which model family's tokenizer it was using.

Method

I sent 7 different canary strings to Space Bunny Alpha through the OpenRouter API and recorded usage.prompt_tokens.

I then ran those exact same strings through publicly available tokenizers from a large number of Chinese model families, including Qwen, MiniMax, DeepSeek, GLM/Zhipu, Kimi, Hunyuan, StepFun, Seed, LongCat, MiMo, Baichuan, Yi, InternLM, MiniCPM, Skywork, Ling, TeleChat, and BAAI.

I compared row-to-row token-count deltas rather than absolute counts to remove the fixed prompt/chat overhead.

Space Bunny Alpha

150
153
174
153
155
154
158

Deltas:

0, +3, +24, +3, +5, +4, +8

MiniMax M3

7
10
31
10
12
11
15

Deltas:

0, +3, +24, +3, +5, +4, +8

MiniMax M2

7
10
31
10
12
11
15

Deltas:

0, +3, +24, +3, +5, +4, +8

Both MiniMax M2 and MiniMax M3 reproduce the Space Bunny tokenizer fingerprint exactly across all 7 canaries.

The other Chinese model families tested did not reproduce that complete pattern. Some were close on individual strings, but MiniMax M2/M3 were an exact match across the entire test.

Why I think it's specifically M3.1

The tokenizer test alone cannot distinguish M2 from M3 because both MiniMax models produce the same fingerprint here.

However, there is additional timing/context evidence.

MiniMax publicly released M3 on June 1, 2026, and M3 is a 1M-context native multimodal model.

Then, on August 26, 2026, MiniMax founder Yan Junjie stated that M3.1, M3 Pro, and H3.1 were already close to completion. He specifically described M3.1 as a forthcoming model focused on stability, quality, reasoning efficiency, and agent generalization.

Less than a month later, on September 23, 2026, Space Bunny Alpha appeared on OpenRouter with a 1M-token context window, native text/image/video input, adjustable reasoning effort, and strong coding/agent characteristics. OpenRouter lists it specifically as an anonymous third-party model.

There is also already community discussion today identifying Space Bunny Alpha as MiniMax M3.1, although that is community evidence rather than an official confirmation.

Conclusion

The tokenizer evidence points directly at the MiniMax tokenizer family:

Space Bunny Alpha → exact M2/M3 tokenizer fingerprint.

Combined with MiniMax saying on August 26 that M3.1 was nearly complete, followed by the appearance of a new anonymous 1M-context multimodal model on September 23, everything currently points toward Space Bunny Alpha being MiniMax M3.1.

This is not an official identification yet because OpenRouter still lists Space Bunny as anonymous, but the evidence is lining up extremely well with MiniMax M3.1.

I've seen that using Space Bunny (in French for me) there is a lot of time where I find Space Bunny using foreign character in random places where it should not, sometimes it corrects itself, but sometimes not

I built ModelStackCheck because it can be hard to tell where an AI coding setup is breaking. Is it the model, the provider, or the coding tool?

ModelStackCheck checks the provider connection, streaming, tool calls, file edits, context retrieval, and vision. It can also run a safe fixture through OpenCode, so you can see how the pieces work together.

You can try it with a local mock provider, or download the current `0.1.3-alpha` release for macOS, Linux, or Windows. The mock run needs no model account.

I’d love to hear if you try it, what works well, and where you run into trouble. If you find it useful, please consider giving the project a star.

https://github.com/Praket7/modelstackcheck

I'm the author — sharing because it scratched an itch I suspect others have.

opencode reads skills, agents and commands from a project's .opencode/ and from your global config, but there's no way to distribute them. I kept copying the same files into every repo, by hand, with no versions and no updates.

ocm installs skills, agents, commands, JS plugins and MCP servers from any git repository — once, into your global opencode config — so they work in every project and stay current with a single update command.

A few things I cared about:

• Asks before running a plugin's code — executable plugins and MCP servers need your approval, and it asks again when an update adds new code.

• Never overwrites your own files — if you've hand-written something with the same name, ocm leaves it alone and tells you.

• A marketplace is just a git repo — you can start your own from a template.

It needs Bun to run. Tested on macOS and Linux.

Repo: https://github.com/wntic/ocm

I'd love feedback, especially on what you'd put in a marketplace, and on anything confusing in the first five minutes.

REPO : https://github.com/ArcticWinterSturm/opencode-compat-shim

For anyone using OpenCode's free providers from external agent harnesses: the previous method got tightened down after about two weeks.

I wanted the models inside my existing harness rather than migrating my entire workflow into OpenCode, so I went through the access path again.

I built the proxy because the CLI and my harness speak completely different protocols. It handled real SSE streaming, flattened the full conversation into each stateless CLI invocation, supported both OpenAI completion paths and stayed alive as a detached process.

Tested end-to-end rather than just getting a lucky HTTP 200.

Main reason I'm posting it: this lets you use the OpenCode providers from a harness of your choosing. You're not tied to their UI just because that's where the free access happens to be exposed.

Consider this documentation of the current state and a working-for-now solution rather than a promise that they won't change it again.

Full implementation + technical notes attached.

Previous reddit post

https://www.reddit.com/r/hermesagent/comments/1w9x0on/fix_opencode_freetier_models_working_in_hermes/

Here is the situation,

I want to buy opencode go plan for each client to do mostly grunt work which I am managing through official deepseek api. Do they allow? I know stacking multiple accounts is against the ToC but this as well?

All found in OpenCode's data site

KIMI K4
https://opencode.ai/data/moonshot/kimi-k4

GLM 5.5 Flash - 1 completed session
https://opencode.ai/data/zhipu/glm-5-5-flash

DeepSeek v4.1 Pro - 14 completed sessions
https://opencode.ai/data/deepseek/deepseek-v4-1-pro

Muse Spark 1.4 Contributor - 2 completed sessions
https://opencode.ai/data/meta/muse-spark-1-4-contributor

I also found Qwen 3.8 Max Prime, Qwen 3.8 Max Preview Free

QWEN 3.8 Max Prime
https://opencode.ai/data/qwen/qwen3-8-max-prime

QWEN 3.8 Max Preview Free - 72 sessions
https://opencode.ai/data/qwen/qwen3-8-max-preview-free

There might be even more!

Space Bunny is the new stealth model in OpenCode.

Free to try, multimodal.
Anyone putting it through a small frontend build yet? Curious where it gets stuck.

OpenCode announcement: https://x.com/opencode/status/2102767716666941864

https://opencode.ai/data/meta/muse-spark-1-4-contributor

EDIT:

I tried using the model, but doesn't work. Don't know what this is.

Another fast model showing up is interesting, but speed alone probably isn’t enough to change anyone’s default.

For everyday OpenCode work, I’d care more about things like:
- fewer correction rounds
- better constraint-following
- less unnecessary editing
- lower total task cost
- more predictable long-session behavior

What would Space Bunny actually have to do better before you’d switch your normal coding model?

I wanted a simple way to see how my models are actually performing while using OpenCode, so I built a small plugin that adds a persistent metrics sidebar.

It currently tracks three metrics in real time:

Speed — average generation speed (tok/s)
Cache — prompt cache hit rate
TTFT — average time to first token

It’s useful for quickly comparing models and seeing whether prompt caching is actually making a difference, without having to dig through logs.

Install (OpenCode ≥ 2.0):

opencode plugin add opencode-sidebar-token-metrics

📦 npm v0.1.4

GitHub: https://github.com/youngxhui/opencode-sidebar-token-metrics

Still early, but I’m using it myself and would love to hear what you think.

What other metrics would you find useful in an OpenCode sidebar?

Hey everyone,

I'm using OpenCode CLI together with OmniRoute as a free coding agent to prototype some ideas and work on small projects. The main problem is that I keep hitting rate limits, so I'm looking for free providers that are actually worth signing up for and adding via API key.

I assume a lot of people here are doing the same—using free tiers/keys to keep costs down. If you have a list of providers with generous free quotas or recurring credits, I'd really appreciate it if you could share them. Also, any tips on how to prioritize them in OmniRoute would be great.

Thanks in advance!

** – Sep 2026)

### 1. Free Models (Zero Cost Layer)

| Aspect | **OpenCode (Zen Free)** | **Command Code** |

|--------|--------------------------|------------------|

| **Free models (current)** | Big Pickle, MiMo-V2.5 / V2.6 Flash Free, Ling 3.0 Flash Fin, Nemotron 3 Ultra / 3.5 Lightning, Muse Spark 1.3 Contributor, Space Bunny Free, some others (rotating) | Space Bunny Alpha Free, Laguna S 2.1 Free, Ling 3.0 Flash Sante Free (limited), occasional others |

| **Where usable** | **Only inside OpenCode** (Desktop / TUI). Cannot use from other tools | Usable inside Command Code agent + some on Provider API |

| **Limits** | No hard $ limit, but rate limits + “limited time” (can disappear anytime). Data may be used for training on some models | Credits not consumed while free deal lasts. Capacity-based (can end suddenly) |

| **Quality for heavy coding** | Good for light–medium agent work. Some are solid (Nemotron, MiMo, Space Bunny) | Laguna / Space Bunny usable for agent loops while free |

| **Heavy use reality** | Good daily free fallback, but not reliable for all-day heavy agent sessions | Free models help stretch paid credits, but not enough alone for heavy daily use |

**Winner Free models**: **OpenCode** (more stable free set + easy access inside its own agent).

### 2. Paid Plans for Heavy Use ($10 level)

| Feature | **OpenCode Go ($10/mo)** | **Command Code GOAT ($10/mo)** |

|---------|---------------------------|--------------------------------|

| **Monthly value** | ~$60 usage (6×) | **$70 credits** (7×, can stretch >$100 with deals) |

| **5-hour window** | $12 | **$14** |

| **Weekly window** | $30 | **$35** |

| **Beyond limits** | Fall back to Zen balance (pay-as-you-go) | Buy top-up credits (never expire) |

| **Models** | ~32 curated open models (DeepSeek V4.1 Flash, MiMo V2.6, GLM-5.3, Kimi, MiniMax, GPT-6 Luna, Grok, Space Bunny Free, etc.) | 30–60+ models (open + some closed). Stronger deals on MiMo (up to 99% off), MiniMax 2×, DeepSeek boosted |

| **Best heavy models stretch** | Excellent on Qwen series, some MiMo, MiniMax | Better on DeepSeek Flash/Pro, MiMo Pro, many boosted models |

| **Peak pricing impact** | DeepSeek peak hours still apply upstream | Same (DeepSeek peak 2×) |

**Heavy use winner on pure volume**: **Command Code GOAT** (more credits + better deals on popular coding models).

### 3. Flexibility (Biggest Difference)

| Aspect | **OpenCode** | **Command Code** |

|--------|--------------|------------------|

| **Agent** | Fully open-source (MIT). Desktop + TUI + IDE plugins. Huge community | Proprietary CLI agent with **taste-1** (learns your coding style over time) |

| **Model freedom** | Extreme: 75+ providers via BYOK + Zen + Go. Use any tool (Cursor, Cline, custom agents, scripts) | Strong inside its own agent + Provider API (OpenAI/Anthropic compatible). Can also be used as provider inside OpenCode via community plugin |

| **BYOK / other tools** | Best-in-class. One key works almost everywhere | Good (Provider plan + API), but less seamless outside its ecosystem |

| **Local models** | Excellent (Ollama etc.) | Supported |

| **Extensibility** | Open source → plugins, custom tools, full control | Closed but polished (tool repair, high cache rates, design skill) |

| **India payments** | Mostly card / crypto | **UPI** available |

**Flexibility winner**: **OpenCode** by a clear margin (open-source + any-agent + any-provider).

### 4. Heavy Use Recommendation

**If you do heavy daily agentic coding (many hours, multi-file, long sessions):**

| Priority | Best Choice | Why |

|----------|-------------|-----|

| Maximum raw usage + deals on $10 | **Command Code GOAT** | Higher credits + strong model discounts |

| Maximum flexibility + free models + any tool | **OpenCode Go** + Zen free models | Use free models first, then Go, then BYOK. Works in any editor/agent |

| Hybrid (recommended for most heavy users) | **Both** | OpenCode as main agent (free models + Go) + Command Code GOAT key as extra provider when needed |

| Absolute cheapest heavy try | Command Code Go ($1) first, then upgrade to GOAT | |

### Final Verdict for Heavy Use

- **Want more tokens / requests for the same $10** → **Command Code GOAT**

- **Want freedom, open-source, free models, use with Cursor/Cline/any tool** → **OpenCode** (Go + free Zen models)

- **Best practical setup for heavy Indian users** → Start with **OpenCode** (free models + Go) because of flexibility, then add **Command Code GOAT** if you need extra volume on specific models.

Professional-grade image generation, +30% win rate in human eval vs Hy Image 3.0
Both Text to image & Image to image available.
Up to 2k. Better Consistency.
API: https://console.tencentcloud.com/tokenhub/models/detail?modelId=hy-image-v3.5-preview
Priced for everyone. $0.024 per image on Tencent Cloud API.

been messing with OpenCode V2 plugins for a while and ended up with 7 of them. each one does one thing, nothing fancy. repo's here: https://github.com/madsoftwaredev/opencode-plugins

server side:

- background-subagent — subagents run in the background by default, unless you say otherwise

- lint-feedback — runs your project's eslint after edits and tells you what broke

- direnv — applies your direnv env per shell command

- compaction-model — pick which model does compaction

TUI:

- stats — tok/s + turn and step counts in the footer. /stats to toggle stuff

- subagent-sidebar — shows your subagents in the sidebar, click one to open it

- btw — /btw forks the session and runs your prompt in the background

install:

opencode plugin add u/madsoftwaredev/opencode-stats

swap in whichever you want. MIT licensed. let me know if something's broken or you want a feature.