Can Kimi K3.1 Pro replace Claude Opus 5.5 in your coding agent?

Moonshot released Kimi K3.1 Pro on 23 October, and one comment in the Hacker News thread (opens in a new tab) asked what I wanted to know: "I'd like to know when I should reach for this model instead of Anthropic's or OpenAI's." On Artificial Analysis it scores 55, three points under Claude Opus 5.5, at half the price per token. That's close enough to test it against Opus for coding-agent work. Most comparisons stop at the price cut and Moonshot's own benchmark table. The independent numbers are messier: two labs ran the same coding benchmark with the same harness and got opposite winners, and that disagreement is what should shape your decision.

TL;DR: For long agent runs your tests can check, yes. On Terminal-Bench 4.0 the two independent labs split the win, so call it a tie, and on Vals AI's run Kimi K3.1 Pro cost about a third as much per task. Keep Claude Opus 5.5 for interactive work and strict specs nothing verifies. It still ranks first overall.

How do Kimi K3.1 Pro and Claude Opus 5.5 compare overall?

Claude Opus 5.5 still ranks first on the Artificial Analysis Intelligence Index, the independent composite of 10 evaluations, with 58. Kimi K3.1 Pro is fourth of 215 models with 55. Opus came out on 22 September, so Kimi arrived a month later. As Simon Willison noted (opens in a new tab), it's the first time a soon-to-be open-weight model has scored this high against the frontier.

For agent work, read the speed and cache rows. Opus writes tokens about twice as fast, which you feel every time you wait on a turn. Cache reads: an agent re-reads its context every turn, and on cached input the two cost exactly the same. Kimi's discount lives in fresh input and output.

Who wins on Terminal-Bench 4.0?

It depends on who runs it. Terminal-Bench 4.0 gives an agent 66 hard tasks in a real terminal, and a task only counts if every test passes. Moonshot's launch table puts Kimi at 65.7 and Opus at 66.4, with Kimi running in the Claude Code harness. That's a vendor table, so I set it aside and went to the two independent runs.

Artificial Analysis (opens in a new tab) ran all 66 tasks with mini-swe-agent, a minimal open-source agent harness, three repeats each, and got Kimi K3.1 Pro 67.2%, Claude Sonnet 5.5 63.6% and Claude Opus 5.5 59.6%. Kimi first, by 7.6 points. Vals AI (opens in a new tab), another independent eval lab, ran the same 66 tasks with the same harness, also three runs, and on 24 October had Opus 5.5 at 65.15% and Kimi at 63.64%, give or take 1.75. Opus first, inside the margin.

Opus's own score moves by more than five points between the two labs, which is more than the gap between the two models on Vals. Same tasks and harness, so the difference sits in each lab's setup. One detail is worth knowing: Artificial Analysis tests Opus with Anthropic's default fallback on, which can route security work to another model, and five of the 66 tasks are security tasks. On that run even Sonnet 5.5 beat Opus, which points at the setup more than the model. I read it as a tie on terminal coding, with your harness, effort setting and task mix deciding the order more than the model name.

Is Kimi K3.1 Pro actually cheaper per task?

On the benchmarks, yes, by more than the per-token price suggests. Vals logged $4.57 per Terminal-Bench test for Kimi K3.1 Pro against $13.20 for Opus 5.5, about a third, and Kimi finished in 49 minutes to Opus's 1h04m. On the Artificial Analysis index it cost $2.11 per task against $5.98. The reason is token count: Artificial Analysis ran Opus at max effort, and Kimi wrote 150M output tokens to run the index against Opus's 260M.

Real bills vary more than benchmark averages. MindStudio's write-up (opens in a new tab) of a 13-task test, run in the same Claude Code harness with only the model swapped, found one front-end task where Kimi's bill reached about 90% of Opus's. Reasoning effort is the first thing to rule out. According to OrcaRouter's comparison (opens in a new tab), Kimi defaults to its highest effort, max, and Opus 5.5 defaults to medium. If you swap the model and change nothing else, you've changed the thinking budget too. Set the effort explicitly on both before you compare costs.

If you pay for Claude Code through a subscription, per-token API prices aren't your bill. This comparison is for API users and for anyone running agents in CI.

Where does Claude Opus 5.5 still win?

Opus 5.5 wins on work where "done" means matching a spec exactly, and on output speed when you're sitting there waiting. On long unattended runs the speed gap mattered less: Kimi finished its Vals runs sooner. In the same 13-task test, a strict design spec had 33 rules: exact colours, font sizes, breakpoints. Opus passed all 33. Kimi passed 31, and its own summary said it had passed all 33. In a task to train a simulated robot to walk, with a free choice of robot, Kimi picked the two-legged half cheetah, which can't tip sideways, and finished in under six minutes; Opus picked the four-legged ant and trained it for nearly an hour. Both choices were within the rules. Kimi took the easier one, which is fine in a cost-bound batch job and a problem when the spec is the point.

Kimi won some of those tasks: the same tester scored it higher on Blender scene composition and a product shot. Peter Gostev (opens in a new tab), who leads AI capability at the evaluation company Arena, tried it on 3D, animation and website tasks and came away less convinced: "At least in these tests, I don't think it's quite there."

That self-report is the part I'd take seriously. I build test-first with coding agents, and an agent that says it passed 33 rules when it passed 31 is exactly why tests are the spec agents need. I'd trust Kimi K3.1 Pro where a test suite grades the work. Where nothing checks the output, I'd pay for Opus.

Who should switch to Kimi K3.1 Pro?

Switch the work your tests can grade, and keep the rest on Opus. My split:

• Move to Kimi K3.1 Pro: long agent runs with a failing test as the target, batch refactors and migrations behind a test suite, CI jobs where the token bill is the constraint.
• Keep on Claude Opus 5.5: interactive pairing where speed matters, design or spec work without a deterministic check, and anything already covered by a Claude subscription.
• Wait for 4 November: if you want to self-host. Moonshot promises the weights by then, with the licence not yet announced. At 2.8 trillion parameters, 104 billion active, self-hosting means a GPU cluster, so most teams will call it through an API either way.

How should you test Kimi K3.1 Pro on your own code?

Kimi exposes an endpoint that speaks Anthropic's API, which is how MindStudio's tester ran it inside Claude Code by swapping only the model string, so you can test it in the agent you already use. Set the effort first: Kimi offers low, high and max, and Opus 5.5 low through max, per OrcaRouter. Pick five tasks from your repository that already have tests, run each on both models at the same effort, and record whether the tests passed, what the run cost and how long it took. Grade the run on the test output and ignore the agent's summary, since that summary is where Kimi claimed 33 of 33.

If the cost per green run on Kimi holds near the third the benchmarks show, route that class of work to it and keep Opus for the rest. I'll keep comparing new models this way on the gabs.app blog. If you're hiring for someone who runs agents this way every day, send me a note.