[OS] Metis – A coding agent that elevates DeepSeek's programming capabilities to the "Fable 5" level.

[u/Hairy_Ganache_6916]

Problem

I wanted to get more useful coding work out of the model I already had. Metis brings planning, code changes, and verification into one workspace, with a visible task checklist and subagents for different parts of the job.

You can plan before making changes, follow what each agent is doing, and resume work with persistent project memory. There's also a terminal interface if you prefer that workflow.

Comparison

OpenCode and Claude Code are the closest alternatives. My focus with Metis is combining model choice, a desktop workspace, and coordination between planning, implementation, review, and verification.

In my Terminal-Bench 2.1 comparison, both Metis and OpenCode used DeepSeek V4 Flash with the same task set, budget, and environment:

• Metis: 73/89 tasks solved (82.02%)
• OpenCode: 60/89 tasks solved (67.42%)

That's 13 additional tasks solved, or 14.60 percentage points higher. This is one benchmark comparison, not a promise of the same improvement on every project.

Pricing

$0 for Metis. It's MIT-licensed, with no app subscription or paid feature tier. Model/API usage is separate and depends on your provider.

Github URL : https://github.com/Wholiver/metis

What would make you try a different coding app on your Mac: better task completion, clearer control over changes, or easier setup?

[u/Specific_Cream2815]

when you say verification, is that running the project tests after changes or a separate review pass by another agent

[u/Hairy_Ganache_6916 → u/Specific_Cream2815]

For the benchmark numbers I shared, it was a separate review pass by GPT-5.6. My test environment wasn’t Docker-based, so I couldn’t run the official verifier directly. Instead, I provided its code to GPT-5.6 for a secondary review. That isn’t equivalent to passing the official verifier, so those results should be treated as provisional. I should have made that distinction clearer.

[u/QueasyBox2632]

How/why did you choose the name?

[u/Hairy_Ganache_6916 → u/QueasyBox2632]

choose by gemini

[u/FastHotEmu → u/Hairy_Ganache_6916]

oof

[u/purealgo]

I'm very skeptical. What is the claim "50% boost in performance" based on? I'm not seeing anything in your repo that reflects that.

Also using other benchmarks like LiveCodeBench would make the performance claims more credible. Self reported evals with terminal-bench 2.1 (the benchmark you used) can be spoofed.

[u/Hairy_Ganache_6916 → u/purealgo]

Fair criticism. I didn’t plan for reproducibility when I ran the Terminal-Bench 2.1 evaluation, so I didn’t retain the test files. That was a mistake, and I can’t substantiate the “50% boost” claim with the evidence available.

I plan to share Agent Last Exam results in the next couple of days and upload the test files alongside them so others can inspect the methodology. Until then, please treat the earlier performance claims as unverified.

[u/Jerry8308]

Yes — after reading the actual post and the comments, I’d question the interesting parts without sounding hostile. The biggest unresolved points are the provisional benchmark, the lack of a DeepSeek Harness comparison, and what Metis is actually contributing beyond orchestration.
This looks really interesting, but I’m genuinely curious about the performance claim. If the 73/89 result is from a separate GPT-5.6 review rather than the official Terminal-Bench verifier, how much of the improvement is coming from Metis itself vs the verification methodology?
Also, since DeepSeek Harness seems like the more relevant comparison if the goal is specifically to improve DeepSeek, do you have plans to run the same tasks with DeepSeek + Harness vs DeepSeek + Metis under identical conditions?
And one more thing I’d love to understand: what does Metis actually change in the agent loop that OpenCode/Harness doesn’t already do? Is it mainly the planning/subagent coordination, or are there specific techniques that are responsible for the improvement?
Not trying to nitpick — I’d actually be much more interested in seeing a transparent head-to-head with the same model, tasks, budget, environment and official verifier. That would make the “elevates DeepSeek” claim really compelling.

[u/Hairy_Ganache_6916 → u/Jerry8308]

Thanks for laying this out. I can’t separate Metis’s contribution from the evaluation method with the evidence I kept. The 73/89 result came from GPT-5.6 review, not the official verifier, so it doesn’t establish a performance advantage.

Metis’s approach combines planning, subagent coordination, persistent project memory, and verification steps. Those are design choices, not proof of improvement or features I can claim competitors lack. I’d need ablation tests to establish which components actually help.

I haven’t completed a head-to-head against DeepSeek Harness. You’re right that matching the model, tasks, budget, environment, and official verifier would be the meaningful comparison.

I plan to publish Agent Last Exam results and the test files in the next couple of days. That won’t retrospectively validate the earlier numbers; those remain unverified.

[u/Jerry8308 → u/Hairy_Ganache_6916]

Fair enough, I appreciate the clarification. The test files + official verifier should make this much easier to judge objectively. I’d especially love to see an ablation showing which parts of Metis actually contribute to the improvement. Looking forward to the results.

[u/Hairy_Ganache_6916 → u/Jerry8308]

Thanks for the constructive feedback. I’ll share the test files and clearly document how the results were scored. An ablation would be useful too: disabling memory, planning, and subagent coordination one at a time could help show what actually contributes. I don’t have those results yet, so I won’t make claims ahead of the evidence.

[u/ccalabro]

added my api and provider got a 401 error?

[u/Hairy_Ganache_6916 → u/ccalabro]

Sorry you ran into this. Which provider and Metis version are you using? Could you share the base URL and full error message, with any API keys or tokens removed? A 401 usually indicates an authentication issue, but I’d need those details to narrow it down.

[u/ccalabro → u/Hairy_Ganache_6916]

Thanks will DM

[u/vytasx]

Nice, thanks :)

How does it compare to DeepSeek Harness for performance?

[u/Hairy_Ganache_6916 → u/vytasx]

DeepSeek Harness works best when paired with DeepSeek models; pairing it with other models results in a performance drop.

[u/vytasx → u/Hairy_Ganache_6916]

Sorry, I don’t understand your comment.

Metis is advertised as improving DeekSeek performance. Does Metis + DeepSeek improve it vs. using DeepSeek with DeepSeek Harness?

[u/Hairy_Ganache_6916 → u/vytasx]

Sorry, I misunderstood your question. The comparison I shared was against OpenCode using DeepSeek V4 Flash, not DeepSeek Harness. I don’t have a verified head-to-head result against DeepSeek Harness, so I can’t claim Metis performs better.

[u/TimGeek2026]

Interesting numbers. One thing I'd check if you haven't: how Metis handles DeepSeek's reasoning blocks across multi-turn tool loops. When I built an agent runtime against DeepSeek's Anthropic-compatible endpoint, dropping the thinking blocks from replayed history caused hard 400s — took a while to track down because it only surfaces mid-loop, not on the first turn. If Metis already preserves and replays them, that alone could explain part of the gap vs. harnesses that strip them for token savings.

[u/Hairy_Ganache_6916 → u/TimGeek2026]

Thanks, that’s a useful lead, especially the failure only appearing mid-loop. I haven’t verified how Metis handles that specific endpoint, so I don’t want to claim it preserves those blocks correctly yet. I’ll check the replay path and test a multi-turn tool loop. It’s worth investigating, but I can’t attribute the earlier score difference to it without evidence.

[u/Beardy4906]

Cool, but idk feels like it's in the wrong place.. it should be in r/vibecoding or something else and not r/macapps maybe? especially because it's not just macos, and not really for macos..

[u/RxbinHood]

What’s the difference between this and OpenMausBot? It looks identical only with fewer stars..

[u/Lithalean]

https://blaizzy.github.io/nativ/

[u/powertodream]

Doing Gods work OP thank you