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5090 is plenty for the Q4_K_M quantized version of 3.6 27B with reduced context size.

I run it on a 3090(24GB) and 64k context using GGUF format and llama-cpp. Double 3090 gives you 128k, quad 3090 gets you to full context - 256k.

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OpenRouter is (roughly) a single proxy between you + many different models + providers. it works with opencode (+ many other products), and is relatively convenient for trying out a bunch of models.

for example, they already have qwen3.8-max

https://openrouter.ai/discover?model=qwen/qwen3.8-max

note that they add some fee ontop of things (maybe 10% of spend?). it isn't htat big of a deal for general experimentation, but if you end up wanting to use a single model in a higher-volume way, it likely makes sense to cut them out of your stack.

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Bedrock seems to have stopped adding new open-weights models, and mostly only has Anthropic and OpenAI stuff now. You can get Qwen 3.8 directly from Alibaba: https://www.qwencloud.com (proprietary variant) or from DigitalOcean (this variant, probably also from others soon).

On your 5090 you could easily run a smaller model like Qwen 3.6 27B: https://huggingface.co/collections/Qwen/qwen36 or Gemma 4 etc., or as mentioned there's a Qwen 3.8 27B coming out in a few days.

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What does the number before the B signify?
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Its number of parameters. The 'B' is billions. If you have bf16 weights each parameter would be 16 bits.
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You could easily run any of their 30B-or-less models which is what most people are waiting for.

Apparently the ~30B variant will be released on Friday?

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Fireworks or OpenCode Go
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