Model comparison · accepted catalogue facts 2026-10-21
Gemini 3.1 Pro Preview vs Kimi K3
A quality score or a computable price is missing. This pair has no better-and-cheaper verdict.
Editorial comparison: Direct benchmark rivals: Gemini 3.1 Pro Preview (Google) vs Kimi K3 (Moonshot AI) with overlapping confidence intervals Inclusion does not recommend either model.
Balanced effective USD / 1M tokens · lower is better
$3.05/M
Price under confirmation since Oct 13, 2026
In-Depth Analysis
Gemini 3.1 Pro Preview vs Kimi K3: Measured Technical Breakdown
Comprehensive comparison across measured human-preference evaluation, effective production token costs, architectural limits, and migration trade-offs.
Measured Capability (LMArena)
Gemini 3.1 Pro Preview leads by 4.7 Elo
Gemini 3.1 Pro Preview: 1480.3 ±2.95 · Kimi K3: 1475.6 ±4.6 Intervals overlap — not a guaranteed quality advantage
Cost Comparison Across Canonical Production Workloads
Rates represent effective cost per 1M tokens under standard token blends. Cached prompt reads are factored according to workload context reuse.
Workload & Ratio
Gemini 3.1 Pro Preview
Kimi K3
Cost Difference
Advantage
Balanced3 tokens in per 1 out
Separately billed reasoning tokens are not part of this token blend.
$3.05/1M tokens
—
Custom quote needed
SummariseHuge input, tiny output
Separately billed reasoning tokens are not part of this token blend.
$1.14/1M tokens
—
Custom quote needed
ChatLong cached system prompt
Separately billed reasoning tokens are not part of this token blend.
$4.38/1M tokens
—
Custom quote needed
Code genOutput dominates
Separately billed reasoning tokens are not part of this token blend.
$6.28/1M tokens
—
Custom quote needed
AgenticContext replayed each turn
Separately billed reasoning tokens are not part of this token blend.
$2.01/1M tokens
—
Custom quote needed
Architectural & Operational Specifications
Specification
Gemini 3.1 Pro Preview
Kimi K3
Operational Note
Context window
1,048,576 tokens
1,048,576 tokens
—
Max output generation
65,536 tokens
943,718 tokens
Kimi K3 allows longer single-turn completions
Base input price
$2.00 / 1M tokens
$0.730 / 1M tokens
Kimi K3 input rate is cheaper
Base output price
$12.00 / 1M tokens
$10.00 / 1M tokens
Kimi K3 output rate is cheaper
Cached input price
$0.200 / 1M tokens
$0.550 / 1M tokens
Gemini 3.1 Pro Preview offers lower cached prompt cost
Reasoning & thinking tokens
Supported; separately billed at $12.00/1M
Supported; standard rates
—
Input modalities
audio, file, image, text, video
text, image, video
—
Tool calling / function use
Supported
Supported
—
Open weights & licence
Proprietary (proprietary)
Open weights (kimi-k3)
Kimi K3 allows independent hosting or local deployment
Provider & reseller market
Google · 6 provider offers
Moonshot AI · 25 provider offers (4.73× spread)
—
When to Choose Gemini 3.1 Pro Preview
Higher measured general capability (1480.3 Elo on human evaluation).
These settings are included in the share link. The fixed-request scenario and private evaluation data below are excluded.
A ↔ B
A quality score or a computable price is missing. This pair has no better-and-cheaper verdict.
Estimated blend: 75% input, 25% output; 0% cached input. Base context tier. Prompt length selects the billing tier. An unlisted cache-read rate uses that tier’s full input rate in this blend; missing required input or output rates prevent an estimate. The fixed-request estimate below validates actual context and output limits and requires a published cache-read rate when cache hits are assumed.
What changes between these models
Quality first, then estimated price. LMArena scores are human-preference measurements, not a benchmark of your application. A missing score is unrated.
Gemini 3.1 Pro Preview · Meets the stated model requirements
Kimi K3 · Meets the stated model requirements
Material differences and unknown evidence. Deltas compare each model with model A. Unknown facts remain visible.
Provider counts and precision flags describe catalogue offers. They do not establish the precision, availability, region, tool behaviour or limits of your chosen endpoint. Open each model’s provider table before switching.
Estimate unavailable: Separately billed reasoning tokens are not part of this token blend.
Separate reasoning: $12/1M tokens; reasoning-token counts are not modelled here. Rates below are USD per 1M tokens. A threshold selects that whole input/output rate pair.
Rates below are USD per 1M tokens. A threshold selects that whole input/output rate pair.
Input-token threshold
Input
Output
Cached input
Base, up to and including first threshold
$0.73
$10
$0.55
Migration preflight · compare each candidate with model A
Keeping Gemini 3.1 Pro Preview is a valid decision. No pairwise comparison certifies a drop-in replacement.
Gemini 3.1 Pro Preview → Kimi K3
Known loss or failed requirement
audio input is not supported by the candidate.
file input is not supported by the candidate.
Provider endpoint, serving precision, availability and task success need your own verification. Catalogue model capabilities do not certify an endpoint.
Private to this tab unless you save locally or explicitly export private details. These are estimates, not observed invoices. Cross-model token counts and task success are assumptions.
0.1 extra attempts means 10 extra full attempts per 100 requests. Cache writes, tool charges, taxes and unlisted charges are excluded.
Gemini 3.1 Pro PreviewEstimated total: unknown Separately billed reasoning tokens are not part of this request shape.
Kimi K3Estimated total: $6.46 1,000 full attempts · base rates
Prompt and output sensitivity · sampled scenarios
Every point recalculates the entire request shape. Tier-boundary samples include one token below, at and above each threshold. Ordering between samples is not guaranteed. Lowest known cost excludes unknown estimates and is not a replacement recommendation.
Vary input; hold output, requests, cache and retries fixed.
Input tokens
Gemini 3.1 Pro Preview
Kimi K3
Coverage
2,000
unknownSeparately billed reasoning tokens are not part of this request shape.
$6.46Lowest known
Incomplete
4,096
unknownSeparately billed reasoning tokens are not part of this request shape.
$7.99008Lowest known
Incomplete
32,768
unknownSeparately billed reasoning tokens are not part of this request shape.
$28.92064Lowest known
Incomplete
131,072
unknownSeparately billed reasoning tokens are not part of this request shape.
$100.68256Lowest known
Incomplete
199,999
unknownSeparately billed reasoning tokens are not part of this request shape.
$150.99927Lowest known
Incomplete
200,000
unknownSeparately billed reasoning tokens are not part of this request shape.
$151Lowest known
Incomplete
200,001
unknownSeparately billed reasoning tokens are not part of this request shape.
$151.00073Lowest known
Incomplete
Vary output; hold input, requests, cache and retries fixed.
Output tokens
Gemini 3.1 Pro Preview
Kimi K3
128
unknownSeparately billed reasoning tokens are not part of this request shape.
$2.74
2,048
unknownSeparately billed reasoning tokens are not part of this request shape.
$21.94
8,192
unknownSeparately billed reasoning tokens are not part of this request shape.
$83.38
Bring your observed evaluation results
JSON is parsed locally. Prompts, filenames, individual responses and extra fields are not retained. Import only aggregate measurements for selected models. Task/version labels do not establish that two evaluations used the same dataset.
Use the exact catalogue ID. Replace the example values with observed measurements. Omit costUsd or latencyMs when they are unknown. No public score is inferred from these observations.
Keep the decision and its evidence
A portable record retains selected facts, complete tier ladders, public requirements and the publication manifest. It also embeds the full permitted public catalogue to verify the input artifact checksum. Files are larger for this reason (up to 2 MB); local storage is limited to 12 records. Team review is local to this browser; there is no hosted collaboration.
Saving is opt-in and includes private review fields. Shared comparison links never include them. Version 1 Check references remain separate and are not overwritten or guessed into this format.
Saved local decisions · 0
No version 2 decision records are stored in this browser.
Questions this page answers
Is Gemini 3.1 Pro Preview a better-and-cheaper replacement for Kimi K3?
A quality score or a computable price is missing. This pair has no better-and-cheaper verdict.
Which model is higher rated: Gemini 3.1 Pro Preview or Kimi K3?
Gemini 3.1 Pro Preview scores higher on LMArena general (1480.3 ±3.0) compared to Kimi K3 (1475.6 ±4.6), a margin of 4.7 Elo points. However, because the 95% confidence intervals overlap, this does not establish an unconditional superiority across all tasks.
Which model is more cost-effective: Gemini 3.1 Pro Preview or Kimi K3?
Gemini 3.1 Pro Preview bills reasoning tokens separately. Direct pricing comparison requires evaluating your specific input/output prompt ratios and reasoning settings.
How do their context windows and generation limits compare?
Both Gemini 3.1 Pro Preview and Kimi K3 provide an identical 1,048,576-token context window. Maximum output generation limits are 65,536 tokens for Gemini 3.1 Pro Preview and 943,718 tokens for Kimi K3.
What capabilities are lost when switching between Gemini 3.1 Pro Preview and Kimi K3?
Switching from Gemini 3.1 Pro Preview to Kimi K3 involves: audio input is not supported by the candidate; file input is not supported by the candidate. Conversely, moving from Kimi K3 to Gemini 3.1 Pro Preview involves: Output limit: 943,718 → 65,536 tokens. Run test suites on your specific prompt templates and tool declarations before cutting over production traffic.
Can Gemini 3.1 Pro Preview or Kimi K3 be self-hosted or deployed privately?
Kimi K3 provides open weights, enabling self-hosting on private GPU infrastructure, local quantization, and private data pipelines. Managed inference is also offered across third-party API providers (6 for Gemini 3.1 Pro Preview, 25 for Kimi K3).
What is included in this comparison?
Accepted model capabilities, context and output limits, complete price-tier ladders, independent LMArena measurements and missing evidence. Provider endpoint precision and application success still need verification.
Can I compare a different workload or keep a decision record?
Yes. Change the public workload, prompt length and requirements in the comparison workspace. Fixed-request scenarios, aggregate evaluations and review notes stay local unless explicitly exported.
