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Reviews and evidence

Kimi K3.1 Pro · Community source · Personal experience

Atomic Agent: A Three.js 3D scene comparison between Kimi K3.1 Pro and GPT-6 Astra

The author had Kimi K3.1 Pro and GPT-6 Astra independently complete a 28-second Avatar-style flying-dragon scene in Three.js inside Atomic Agent using the same prompt. Kimi took longer but used fewer steps; using the older K3's Moonshot rates, the author estimated its cost at $1.1–$1.4, compared with about $2.63 for Astra.

Community sourcePersonal experienceEdited 2026-10-24

Test conditions

Model and version
Early-access Kimi K3.1 Pro; GPT-6 Astra as the comparison model.
Environment and client
Atomic Agent, which the author described as an open-source Agent they helped develop.
Reasoning and parameters
Kimi K3.1 Pro accepts only temperature: 1. The Agent's primary call had sent 0.2; the author forced the primary call to use 1, but the image-review tool still used 0.2. Astra's full parameters were not disclosed.

Key data and applicable tasks

One-sentence takeaway

The author had Kimi K3.1 Pro and GPT-6 Astra independently complete a 28-second Avatar-style flying-dragon scene in Three.js inside Atomic Agent using the same prompt. Kimi took longer but used fewer steps; using the older K3's Moonshot rates, the author estimated its cost at $1.1–$1.4, compared with about $2.63 for Astra.

This was not a fair visual benchmark: Kimi's image-review calls failed twice because of an invalid temperature value, so it could not see its own renders; Astra could see its renders and fixed them four times.

Use cases

  • Tasks this can help assess: Performance during a single Agent loop that generates a Three.js scene, writes code, calls tools, and writes its own test scripts.

  • Tasks this should not be generalized to: General programming ability, stable visual-quality rankings, fair model benchmarks, all Agent harnesses, or a definitive cost-savings multiple.

  • Applicable model versions: Early-access Kimi K3.1 Pro; GPT-6 Astra as the comparison model.

  • Test environment or client: Atomic Agent, which the author described as an open-source Agent they helped develop.

  • Reasoning tier and parameters: Kimi K3.1 Pro accepts only temperature: 1. The Agent's primary call had sent 0.2; the author forced the primary call to use 1, but the image-review tool still used 0.2. Astra's full parameters were not disclosed.

Evaluation method

The author gave Kimi K3.1 Pro and GPT-6 Astra the same prompt: build a 28-second Avatar-style flying-dragon scene in Three.js in a single HTML file.

The scene included a Toruk, a rider, six camera angles, a waterfall, a nighttime jungle, and a sunrise. Its geometry and textures all had to be written in code.

Both models ran independently in an Agent loop until the model itself judged the task complete.

The author recorded wall-clock time, step count, tool-call count, and cost estimates. Kimi also wrote a headless-browser script that rendered seven test frames and checked console errors; the author said it had not been asked to do this.

These records did not disclose the complete prompt, Agent configuration, tool definitions, step-by-step traces, original billing details, or a reproducible experiment package.

Key results

The main post reported the following run data:

ModelWall-clock timeStepsTool callsCost
Kimi K3.1 Pro12:282023Author's estimate: $1.1–$1.4
GPT-6 Astra9:1735Not specifiedAbout $2.63

Kimi's cost was not a bill calculated using a public K3.1 Pro price. The author explicitly said that no K3.1 price had been made public at the time, so they estimated it using K3's Moonshot rates. The roughly $2.63 figure for Astra also came without a complete billing breakdown or calculation.

Of Kimi's 49.2K output tokens, the author said 27.7K were reasoning tokens.

Kimi completed the entire 746-line scene code in several large writes rather than making many small edits.

The author considered Kimi's generated scene broadly successful, but one two-second sunrise segment rendered as a flat cyan-green image.

Raw data

The author's original task description was: the two models used the same prompt to generate a 28-second Avatar-style flying-dragon scene in Three.js in a single HTML file, with each model running independently in an Agent loop.

Kimi's original run record was “12:28 wall time, 20 steps, 23 tool calls”; Astra's original run record was “9:17” and it “needed 35 steps”.

Kimi's original cost wording was “About $1.1 to $1.4 by my estimate”. The author also noted “no public K3.1 price yet” and said they used K3's Moonshot rates; Astra's original cost wording was “Astra came out around $2.63”.

Kimi's original wording for reasoning tokens was “27.7K of its 49.2K output tokens were reasoning”, while the code output was described as “the whole 746-line scene”.

Kimi wrote a headless-browser script that rendered seven test frames and checked console errors.

The parameter failure occurred in the image-review tool: the Agent sent temperature: 0.2, which Kimi does not accept.

The author said the primary call was forced to use temperature: 1, but the image-review tool retained the old value.

As a result, Kimi's two image-review calls failed, and it did not see its own screenshots before completing the task.

Astra could see its own renders and, according to the author, fixed them four times.

The author said they were fixing temperature handling so they could run the comparison again.

Verification of author replies

Visible comments on the main post included questions about the visual quality of “fictional objects” and the rider, as well as comments supporting Kimi. After the two “more replies” threads were expanded, the replies included authors such as anonanon9955, vinis_artstreaks, frogchungus, and latent_lurker8587.

No subsequent reply from GapNew4766 was found in the main post, the two expandable reply threads, or the visible comments.

The comments were therefore not presented as new conclusions from the author, and no run data beyond the main post was added.

Conclusions and limitations

  • This is a field report from a single Agent task. It can describe Kimi's execution trace and tool behavior in this Three.js scene task.

  • Kimi took 3:11 longer in wall-clock time than Astra but used 15 fewer steps. Only Kimi's complete tool-call count of 23 was disclosed, so tool-call efficiency cannot be compared on this basis.

  • The cost range came from an estimate using K3's older Moonshot rates and cannot be treated as K3.1 Pro's public price or an actual bill.

  • The price difference calculated from the public ranges can only be treated as an observation about the author's estimate; it cannot be called a definitive “2x savings”.

  • The two models had different visual-feedback conditions: Kimi did not see two screenshots, while Astra did and fixed its output four times. This cannot be called a fair benchmark.

  • There is an author-identified connection between Kimi's flat cyan-green sunrise segment and the failed image review, but no rerun result after the fix was provided.

  • The result covers only one 28-second Three.js task with a single HTML file and code-generated geometry and textures. It cannot be generalized to front-end development in general or to a range of Agent tasks.

Reproduction notes

Reproduction would require the same Atomic Agent version, access to Kimi K3.1 Pro and GPT-6 Astra, the complete prompt, tool definitions, HTML output constraints, stopping conditions, and cost-calculation conventions.

All Kimi calls would also need to use temperature: 1 consistently so that the image-review tool would not continue sending 0.2.

Each step's messages, tool calls, tokens, wall-clock time, costs, seven test frames, and console logs should be saved separately.

To compare visual repair ability, both models should also have the same screenshot-viewing capability, the same number of repair opportunities, and the same stopping rules.

The original post provides enough public information to verify the task description, Kimi's 12:28/20-step/23-tool-call run, Astra's 9:17/35-step run, the original cost estimates, and the parameter failure. It does not provide enough information for a rigorous fair reproduction.

What this supports

  • Performance during a single Agent loop that generates a Three.js scene, writes code, calls tools, and writes its own test scripts.

What this does not support

  • General programming ability, stable visual-quality rankings, fair model benchmarks, all Agent harnesses, or a definitive cost-savings multiple.

Method, limits, and reproduction

The figures, task set, reasoning tier, and client conditions apply only to the listed source and collection snapshot. Different versions, harnesses, or providers must not be compared directly; undisclosed parameters remain unknown.

For a reproduction, fix the model version, provider or client, reasoning tier, tools, task-set version, sample count, and collection date, and record failures, retries, and human corrections. Full steps are in the source notes below.

Original source

Reddit, r/kimi · GapNew4766 · Original publication date 2026-10-24 · Site edit date 2026-10-24

Open original source

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