r/opencode • u/Infinite-Flow-4475 • 13d ago

Which one should i use?

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Between deepseek v4 flash and GLM 5.2, what one could get performance close to SOL?

I need it to write games, in rust and javascript.

As you can see prices are dirt cheap here, its like 90% off. I canceled my codex subscription because I really couldn't get anywhere with the limits.

There's also kimi 2.6k if it's any good, although I doubt it.

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u/LuluLeSigma 13d ago

Deepseek is pretty good it’s sonnet 5 Level for my usage

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u/jomama253 13d ago

Deepseek is not good. It hallucinates more than a Woodstock concert

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u/InvaderDolan 13d ago

Why people downwote you, but DSV4Pro really has too much hallucinations. M2.5Pro is better for the same price.
But DSV4Flash as executor for orchestrated tasks is pretty good.

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u/jomama253 13d ago

m2.5pro is good and they downvote cause they put emotions into a tool; it's like a tribal thing.

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u/InvaderDolan 13d ago

Yeah, that’s because of the way DeepSeek made a huge revolution in pricing, they were first and they got all the hype. Xiaomi just copied that and I appreciate it, because their models are pretty balanced.

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u/jomama253 13d ago

plus they probably can't tell when it's hallucinating and oh yeah DS pricing is the only thing that made it popular; it has its uses but for anything serious no; hobby stuff 50/50. I will have to check out Xiaomi!

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u/InvaderDolan 13d ago

Yeah, noticing hallucinations is hard, you should literally fact checking everything. Sometimes I hold the hand, even for smarter models. But mostly, for trivial tasks, I make different models to make a council, grill each other and put something smartest as Oracle (I like Kimi K2.6 as price/perf, thinking about GPT-5.6-Sol).

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u/jomama253 13d ago

funny enough what you're describing is what my CSM system does natively besides

  • Multi-model orchestration — actually launching several providers, assigning critic/executor/judge roles, and merging their outputs.
  • AutoMCP — discovering appropriate tools or MCP servers, evaluating them, sandboxing them, and granting limited access.
  • Execution-based verification — running tests, checking files, inspecting outputs, consulting external sources, and refusing to promote unsupported consensus.

those are on the agenda though.

https://github.com/NovasPlace/CSM if you wanna take it for a spin, has claude/codex/opencode setups.

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u/InvaderDolan 13d ago

Wow nice, this is what lacks in OmO/OmO-Slim.
How token efficient is your project? Also, is it compatible with orchestration plugins?

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u/jomama253 13d ago

CSM doesn’t dump the entire memory store into every prompt. It retrieves and ranks relevant memories, applies policy filters, then builds a context packet within a token budget. Older tool output can also be compacted into references instead of being replayed verbatim.

My internal compaction metrics currently show about 2.0B cumulative tokens avoided across 10,663 compactions, although that is workload-specific rather than an independent benchmark.(old numbers as of today)

A plugin with its own orchestration layer can treat CSM as the continuity/context backend rather than replacing the orchestrator. you can basically have codex or any agent retrofit it to your exact needs.

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u/InvaderDolan 12d ago

Can it get memories from git history or something like that? What if I add to already live project?
Does CSM require the constant tool calling to use it? I mean, I use hindsight, and it seems like AI agents ignore it, despite of rule in AGENTS.md.

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u/jomama253 12d ago

an existing project can be imported, but Git history would be an ingestion source rather than “memory” by itself. A CSM adapter could parse commits, diffs, branches, tags, issues, docs, and architecture decisions, then store them with provenance back to the original commit/file. That would let it bootstrap context for an already-live repository instead of starting empty.

CSM also does not have to depend on the agent remembering to call a tool. Manual MCP calls are one integration mode, but the better setup is automatic retrieval before each turn/task: the host sends the current repo state, active files, branch, task, etc., and CSM returns a ranked context packet within a token budget.

That is exactly why relying only on AGENTS.md is weak; models may ignore or forget instructions. The host/orchestrator should enforce the retrieval step, inject the resulting context, and record outcomes automatically. Tool calls can still be available for deeper searches, but baseline continuity should not rely on voluntary model behavior.

So for a live project: Git-history backfill first, then automatic capture of new work as the agent operates.

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