Kimi K3.1 Pro Review: We Tested It Against Kimi K3
Last Updated:
2026-10-24
Kimi K3.1 Pro Review: We Tested It Against Kimi K3
Kimi K3.1 Pro is almost on par with Claude Opus 5.5 in coding, while costing half as much per token, according to Moonshot's benchmarks.
To put that claim to the test, we've run a series of tests with the new model, giving it challenging prompts — and compared it directly with its predecessor. In this article you'll learn:
What's new in Kimi K3.1 Pro
How it compares to Kimi K3 and other frontier models
How it performed in our own tests, where we ran both Kimi models on the same tasks inside Overchat AI.
Kimi K3.1 Pro is a big upgrade over Kimi K3, and it's cheaper per token. In our tests, though, Kimi K3.1 Pro took about twice as long to deliver an answer, making it a more situational choice than a drop-in replacement. However, the new model showed its advantage in code, where it built more detailed apps from a single prompt than Kimi K3.
What is Kimi K3.1 Pro?
Kimi K3.1 Pro is a large language model developed by Moonshot AI, a Beijing-based AI company, and the first model in its new K3.1 series. It was released on October 23, 2026.
To create K3.1 Pro, Moonshot took Kimi K3 and trained it further with much more post-training compute, so the model has the same size of 2.8 trillion parameters (104 billion of them active at a time) and the same context window of 1 million tokens.
Kimi K3.1 Pro is a thinking-only model, which means it always reasons before answering (there's no option to turn it off). It accepts text, images and video and generates text. The model comes in two versions:
Kimi K3.1 Pro (API name kimi-k3.1-pro) is available on Kimi.com, in the Kimi apps, Kimi Work, Kimi Code, the Kimi API and third-party apps such as Overchat AI.
Kimi K3.1 Pro Highspeed is the same model running two to three times faster, which costs twice as much and requires the Pro plan in Kimi.
Moonshot has also promised to release the open weights of Kimi K3.1 Pro by November 4, 2026, so you'll be able to run the model locally once the open weights become available, although it will require nearly datacenter-grade hardware to run at any sort of usable speeds. This is not a model optimized for local deployment, but for frontier-grade performance at low costs compared with the proprietary flagships. So does it deliver on that promise?
Kimi K3.1 Pro benchmarks
Let's look at the benchmarks first:
Benchmark
Kimi K3.1 Pro
Claude Opus 5.5
GPT-6 Astra
Claude Fable 5.1
DeepSeek V4.1 Flash
Terminal-Bench 4.0
65.7%
66.4%
58.2%
57.9%
42.3%
SWE Marathon v1.1
51.7%
46.3%
42.5%
45.6%
40.0%
DeepSWE v1.1
75.5%
74.2%
74.1%
67.4%
77.0%
HLE-Full, with tools
70.0%
67.7%
57.2%
65.6%
58.8%
BrowseComp
92.1%
90.8%
91.5%
—
—
OfficeQA Pro v2
64.4%
62.2%
54.4%
54.5%
40.4%
GDPval-AA v2.1, Elo
1,846
1,866
1,573
1,754
1,746
GPQA-Diamond
94.2%
93.9%
96.1%
93.7%
92.2%
Comparing Kimi K3.1 Pro with the leading AI models from Anthropic, OpenAI, and DeepSeek, you can see that the model really offers frontier-grade intelligence, even beating the other flagships on some benchmarks, such as long coding tasks (SWE Marathon), and it's less than a point behind Claude Opus 5.5 on Terminal-Bench, a set of tasks in a command-line environment. That's a huge jump from Kimi K3, which scored only 13% on the same test.
The results above are taken from the Kimi K3.1 release post, and benchmarks released by the vendor often overstate how good the performance is (it's marketing, after all), but in this case independent tests are in agreement. According to Artificial Analysis, for example, in the Intelligence Index, Kimi K3.1 Pro scores 55, which puts it in fourth place behind Claude Opus 5.5 (58), Claude Sonnet 5.5 (56) and Muse Wonder Full (56). If Moonshot releases the weights as promised, it will become the strongest open-weights model on the index.
We tested Kimi K3.1 Pro and Kimi K3 in Overchat AI
To see how much of an upgrade the new model is in practice, we ran Kimi K3.1 Pro and Kimi K3 on the same set of tasks inside Overchat AI.
Logic and trick questions
We wrote new logic questions for this test, but modeled them on popular LLM tests, so the models couldn't just recite answers they had seen during training. Each question was asked twice:
Question
Correct answer
Kimi K3.1 Pro
Kimi K3
Nadia has 3 brothers and 2 sisters, and her brother Leo also has a half-sister from his father's second marriage. How many sisters does Leo have?
4
✅ 2/2
✅ 2/2
River crossing with a boat that fits the farmer, the wolf, the goat and the cabbage at once
1 crossing
✅ 2/2
✅ 2/2
4 ice cubes go into 95 °C tea at 8:00, 3 more at 8:02, 2 are taken out at 8:05. How many whole cubes are in the mug at 8:45?
0
✅ 2/2
✅ 2/2
The plot of "The Glass Lighthouse of Tokyo", a novel by Haruki Murakami
The book doesn't exist
✅ 2/2
✅ 2/2
How to use itertools.window() in Python
The function doesn't exist
✅ 2/2
✅ 2/2
Both models solved every question, including the ones built to catch memorized answers.
Kimi K3.1 Pro in Overchat AI
The only difference in this case was verbosity, where Kimi K3.1 Pro usually gave the answer in the first line and stopped there, while Kimi K3 explained more, for example, it called the arithmetic in the ice cube question "a red herring". For the itertools question, Kimi K3 offered three working alternatives, and Kimi K3.1 Pro gave one.
Hardly anyone likes a verbose model, so getting the answer in the first line without any fluff is a big workflow improvement.
Writing
For the writing task, we asked both models for the opening scene of a cozy mystery, about 250 words long, set in a café inside a working lighthouse on the Scottish coast. The scene had to introduce the owner, one regular customer and the first odd detail that hints at the mystery.
Here's an excerpt from Kimi K3.1 Pro's text. The whole scene contains 228 words, and the model wrote it in 105 seconds:
The lighthouse at Craigvar Point had guarded the same vicious stretch of Scottish coast for 118 years. Nell Craig had run the café in its old engine room for nine, and her fruit scones had inspired almost as much confidence.
At eight, Duncan Reid arrived with the punctuality of a man who had retired from the harbour but not from supervising it. He hung up his oilskin and made for his usual table.
On his table stood a mug of tea, steam curling from its surface. Beside it sat a scone, split and buttered, crust trimmed off—the precise and faintly shameful way he liked it. Nell had unlocked the café herself less than a minute ago.
"Well," he said, "if we're being haunted, at least it's by someone who can butter a scone."
And here's an excerpt from Kimi K3's text. The whole scene contains 265 words, and the model wrote it in 62 seconds:
The Kersaig light had been warning ships off the west coast since 1887. Morag Beaton had been warning customers off the decaf since 2011, and she considered her record the better of the two.
Tam Murchison came in at six-fifteen, as he had every morning since the ferry stopped and he'd run out of things to do. He took his coffee black, his rowie warm, and the Atlantic's behaviour personally, and he sat at the window to keep an eye on all three.
The tower door stood open a hand's width. Its padlock — the Board's padlock, the one Morag had no key to — hung neatly on its hasp. On the third step of the stair, in full view of the gulls, sat one of Morag's own takeaway cups. Black coffee, no lid, still steaming.
"Weel," he said. "Either the Board's come early, or the light's developed a caffeine problem."
In terms of instruction following, both models stuck to the prompt closely, but doesn't K3.1 Pro's tone have a literary quality to it that the other model lacks?
Coding
We gave both models two visual coding tasks. Kimi K3.1 Pro is always on the left and Kimi K3 is on the right.
The first task was an aquarium simulation:
Create a single self-contained HTML file (no external libraries) with a beautiful aquarium simulation on a full-window canvas. Include a school of fish that move with flocking behaviour (separation, alignment, cohesion), a few larger fish that the small ones avoid, swaying seaweed, rising bubbles, light rays from the surface and a sandy bottom. Clicking anywhere drops food pellets that sink slowly, and nearby fish swim to eat them. It must start automatically and run smoothly. Return only the complete code in a single ```html code block.
Kimi K3.1 Pro (left) and Kimi K3 (right), aquarium simulation
The second task was a 3D scene built with Three.js:
Create a single HTML file with an animated 3D scene using Three.js. Load it with an import map from https://cdn.jsdelivr.net/npm/three@0.160.0/build/three.module.js (addons, if you need them, from https://cdn.jsdelivr.net/npm/three@0.160.0/examples/jsm/); no other libraries. The scene: a small low-poly tropical island in the ocean with palm trees, a wooden hut, a pier and a sailboat. Animate a full day-night cycle every 30 seconds: the sun and moon move across the sky, the sky colours change, stars appear at night and the hut's windows light up. The water should have gentle animated waves. The camera slowly orbits the island. Full-window canvas, starts automatically. Return only the complete code in a single ```html code block.
Kimi K3.1 Pro (left) and Kimi K3 (right), 3D island with a day-night cycle
During the day, Kimi K3.1 Pro's island looks more detailed, with more palm trees, rocks, soft shadows and a better-looking sailboat. At night, though, its sky turns almost black and the stars from the prompt never appear. Kimi K3's island is simpler, but its night has stars, and a lamp on the pier is reflected in the water.
Kimi K3.1 Pro sure added extra detail, but it took the model a lot longer to complete these scenes. It wrote almost twice as much code as Kimi K3 (about 33,000 characters against 19,000 for the aquarium), but it took 10.6 and 11.6 minutes to finish the two tasks, while Kimi K3 needed 3 and 4.1 minutes.
Speed
Kimi K3.1 Pro was slower than Kimi K3 in every task. Most of the difference comes from reasoning: Kimi K3.1 Pro always thinks at maximum effort by default, so it spends more time before the first word of the answer appears, even on simple questions.
Task
Kimi K3.1 Pro
Kimi K3
Logic and math questions, median
13 s
6 s
Writing
105 s
62 s
Aquarium code
10.6 min
3 min
3D island code
11.6 min
4.1 min
If speed matters, Moonshot offers Kimi K3.1 Pro Highspeed, which runs two to three times faster, but it costs twice as much per token.
Which is better: Kimi K3.1 Pro or Kimi K3?
Kimi K3.1 Pro is the better model of the two. It scores 11 points higher on the Artificial Analysis Intelligence Index, hallucinates much less often, costs a third less per token in the API, and in our coding tests it built more detailed and more accurate apps.
For everyday questions, though, the upgrade is hard to notice. Both models solved every logic, math and instruction-following task, and Kimi K3 did it twice as fast. So Kimi K3.1 Pro is worth it for coding and complex agentic tasks, where it has time to think, while for quick chat questions Kimi K3 gives the same answers sooner.
The Best Kimi K3.1 Pro alternatives
If you want a similar level of performance from another AI model, here's the list of alternatives you might consider:
Model
Developer
Intelligence Index
Input, per 1M tokens
Output, per 1M tokens
Overchat AI, per message
Claude Opus 5.5
Anthropic
58
$4
$20
110 credits
Claude Sonnet 5.5
Anthropic
56
$2
$10
4 credits
Kimi K3.1 Pro
Moonshot AI
55
$2
$10
16 credits
GPT-6 Astra
OpenAI
53
$10
$50
3 credits
Muse Wonder
Meta
52
$4
$20
5 credits
DeepSeek V4.1 Flash
DeepSeek
45
$0.15
$0.60
1 credit
Claude Opus 5.5
Claude Opus 5.5 is Anthropic's flagship model and the leader of the Intelligence Index. It's slightly ahead of Kimi K3.1 Pro on Terminal-Bench, but costs twice as much per token. You can use Claude Opus 5.5 in Overchat AI.
Spec
Value
Developer
Anthropic
Intelligence Index
58
Context window
1M tokens
API price, input per 1M tokens
$4
API price, output per 1M tokens
$20
Price per message in Overchat AI
110 credits
Claude Sonnet 5.5
Claude Sonnet 5.5 is a smaller Claude model with the same API price as Kimi K3.1 Pro and one point more on the Intelligence Index. You can use Claude Sonnet 5.5 in Overchat AI.
Spec
Value
Developer
Anthropic
Intelligence Index
56
Context window
1M tokens
API price, input per 1M tokens
$2
API price, output per 1M tokens
$10
Price per message in Overchat AI
4 credits
GPT-6 Astra
GPT-6 Astra is OpenAI's model with the lowest hallucination rate in Moonshot's comparison (5.5%). It's the most expensive model in the API, but one of the cheapest in Overchat AI.
Spec
Value
Developer
OpenAI
Intelligence Index
53
Context window
1.05M tokens
API price, input per 1M tokens
$10
API price, output per 1M tokens
$50
Price per message in Overchat AI
3 credits
Muse Wonder
Muse Wonder is Meta's first frontier model. When we tested Muse Wonder, it answered most questions in 5 to 12 seconds, which makes it a much faster option than Kimi K3.1 Pro. You can use Muse Wonder in Overchat AI.
Spec
Value
Developer
Meta
Intelligence Index
52
Context window
1M tokens
API price, input per 1M tokens
$4
API price, output per 1M tokens
$20
Price per message in Overchat AI
5 credits
DeepSeek V4.1 Flash
DeepSeek V4.1 Flash is the budget alternative: ten points lower on the Intelligence Index, but more than ten times cheaper per token. You can use DeepSeek V4.1 Flash in Overchat AI.
Spec
Value
Developer
DeepSeek
Intelligence Index
45
Context window
1M tokens
API price, input per 1M tokens
$0.15
API price, output per 1M tokens
$0.60
Price per message in Overchat AI
1 credit
FAQ
What is Kimi K3.1 Pro?
Kimi K3.1 Pro is a large language model from Moonshot AI, released on October 23, 2026. It's a version of Kimi K3 trained with more post-training compute, with 2.8 trillion parameters and a context window of 1 million tokens.
Is Kimi K3.1 Pro open source?
Not yet. Moonshot has promised to release the open weights of Kimi K3.1 Pro by November 4, 2026. Until then, the model is available on Kimi.com, in the Kimi apps, through the Kimi API and in third-party apps such as Overchat AI.
How much does Kimi K3.1 Pro cost?
In the Kimi API, Kimi K3.1 Pro costs $2 per million input tokens and $10 per million output tokens, a third less than Kimi K3. Kimi K3.1 Pro Highspeed costs $4 and $20. In Overchat AI, one message to Kimi K3.1 Pro costs 16 credits.
What is Kimi K3.1 Pro Highspeed?
Kimi K3.1 Pro Highspeed is the same model as Kimi K3.1 Pro, running two to three times faster. It costs twice as much per token and requires the Pro plan or higher in Kimi.
Where can I use Kimi K3.1 Pro?
You can use Kimi K3.1 Pro on Kimi.com, in the Kimi apps for iOS and Android, in Kimi Work and Kimi Code, through the Kimi API and in Overchat AI, where it's available in the model selector next to Kimi K3.