MModelspectraIndependent AI Model Intelligence
Head-to-head · Updated 2026-09-08
Model Comparison · Head to Head

Kimi K3 vs MiniMax M3

Kimi K3 wins on Overall, Coding, Multimodal. Every numeric field is compared below, with a worked monthly-cost example and a pick rule for each use case.

VendorMoonshot AI / MiniMax
Data fields15+ dimensions
Updated2026-09-08
Read~9 min
01

Verdict at a glance

Bottom line: Choose Kimi K3 when coding depth, long-context reliability, lower refusal matter most; choose MiniMax M3 when lower cost, lower latency, fine-tuning/ecosystem is the priority.

Choose Kimi K3 if you…

  • Best-in-class long text
  • Open-source and self-hostable
  • Strong codebase understanding
  • Fair price
  • Best for: Long-document reading, Codebase analysis, Chinese

Choose MiniMax M3 if you…

  • Strong agent ability
  • Open source
  • Low price
  • Best for: AI agents, Open source, Chinese
02

Head-to-head aggregate scores

Scores are 0–100, aggregated from public benchmark information and independently weighted across three leaderboards. Rank is out of 22 tracked models.

Kimi K3 Higher overall
Moonshot AI · #8 overall
Overall77
Coding71
Multimodal81
VS
MiniMax M3
MiniMax · #13 overall
Overall70
Coding68
Multimodal70

Aggregated from public sources and independently weighted; methodology on the Terms page. Scores within 3 points are treated as statistically tied.

03

Specs & pricing — every field side by side

List API prices in USD per 1M tokens. The highlighted cell is the stronger value/capability on that row.

DimensionKimi K3MiniMax M3Verdict
VendorMoonshot AI (CN)MiniMax (CN)Different vendors
Released2026.062026.06MiniMax M3 is newer
Overall (rank)77 · #870 · #13Kimi K3 +7
Coding71 · #1168 · #13Kimi K3 +3
Multimodal81 · #1070 · #18Kimi K3 +11
Context window256K1MMiniMax M3 larger
Max output64K64KTie
Effective-context9990Kimi K3 more reliable
Input $/1M$3$0.6MiniMax M3 cheaper
Output $/1M$15$2.4MiniMax M3 cheaper
Cache discountcustomnoneMiniMax M3 deeper
Speed~45 tok/s~60 tok/sMiniMax M3 faster
TTFT0.7s0.5sMiniMax M3 snappier
Function calling8084MiniMax M3 ahead
Refusal rate~6%~7%Kimi K3 less restrictive
English7570Kimi K3
Chinese9288Kimi K3
Modalitiestext, imagetextdifferent coverage
Open weightsYesYesBoth open
Fine-tuningNoYes
Free tierKimi App free; free quota on the open platformHailuo AI free; open-platform quota
SOC2 / no-trainno / yesno / yes
Private deploymentYesYesBoth support it

Fields drawn from vendor public documentation and the Modelspectra 22-model dataset; speed varies with network, concurrency and prompt length. Verify current pricing before purchase.

04

Dimension-by-dimension analysis

Reasoning & overall intelligence

Kimi K3 leads the overall aggregate by 7 points (77 vs 70). That is a meaningful, not marginal, edge on hard, multi-step reasoning, while MiniMax M3 remains a strong generalist that is not out of its depth on routine work.

Agentic coding

This is a modest gap: Kimi K3 scores 71 against 68. On multi-file edits, SWE-style tickets and long-horizon agent loops Kimi K3 needs fewer correction turns; MiniMax M3 is still competent for scripts and assisted completion but trails as task complexity rises.

Multimodal

Kimi K3 leads multimodal 81 vs 70. A concrete modality difference: Kimi K3 additionally handles image. Neither emits native video, so the comparison is about parsing images and documents, not generation.

Speed & latency

MiniMax M3 is faster in interactive use: ~60 tok/s with 0.5s TTFT versus ~45 tok/s with 0.7s TTFT (about 1.3× the throughput). For conversational UIs where perceived responsiveness drives retention, that edge is a real product factor even when raw reasoning is lower.

Context: window vs usable recall

Nominal windows are 256K for Kimi K3 and 1M for MiniMax M3. Crucially, the larger nominal window does not win on usable recall: MiniMax M3 advertises 1M but Kimi K3 scores higher on effective-context (99 vs 90), i.e. it actually retains more of what it was given.

Price & total cost

MiniMax M3 is the cheaper API at $0.6/$2.4 versus Kimi K3 at $3/$15 per 1M input/output tokens — list input is about 5.0× lower.

Chinese vs English

English: Kimi K3 75 vs MiniMax M3 70. Chinese: 92 vs 88. For Chinese-language production, Kimi K3 is the stronger pick. Note that non-Chinese models generally require overseas network access for their APIs.

Tool use & ecosystem

Function-calling score: Kimi K3 80 vs MiniMax M3 84, so MiniMax M3 has the edge on structured tool use. Fine-tuning is available from MiniMax M3. Factor in existing SDK/plugin familiarity — switching cost often outweighs a few-point tool-use gap.

05

Cost worked example — same workload, real token math

Assume a production workload of 100M input + 30M output tokens per month, with 90% of input tokens served from cache. Figures use public list prices.

Scenario · per monthKimi K3MiniMax M3Gap
List priceno cache applied$750100M in × $3  +  30M out × $15$132100M in × $0.6  +  30M out × $2.45.68×gap
With caching90% of inputs cache-hit$750no published cache discount$132no published cache discount5.68×gap

Illustrative model; your input/output mix and cache-hit ratio change the result. Prices are list rates before any enterprise agreement.

06

Decision tree

IF the workload is agentic or multi-file coding and a wrong first pass is expensive  →  choose Kimi K3 (coding 71 vs 68).
IF you serve real-time users and latency is a product KPI  →  choose MiniMax M3 (~60 tok/s, 0.5s TTFT).
IF you are cost-driven at scale on routine, high-volume workloads  →  choose MiniMax M3 ($$0.6/$$2.4 per 1M in/out).
IF long-document recall has to be near-perfect  →  choose Kimi K3 (effective context 99 vs 90).
07

Frequently asked questions

Is Kimi K3 worth the higher price over MiniMax M3?
At list the input rate is 5.0x higher, but cache discounts and output pricing narrow the effective gap. Pay the premium when Kimi K3's stronger dimensions protect revenue; for routine volume MiniMax M3 is the economical pick.
How do costs compare at 100M tokens/month with caching?
At 100M input + 30M output with 90% of inputs cache-hit, Kimi K3 is about $750/month and MiniMax M3 about $132/month after cache discounts ($750 and $132 at list).
Does the bigger context window actually matter?
Nominal windows are Kimi K3 (256K) and MiniMax M3 (1M), but usable recall follows the effective-context score (99 vs 90). Prefer the higher effective-context model for long-document work where nothing can be missed.
Which one supports fine-tuning?
MiniMax M3 supports fine-tuning; Kimi K3 does not at this tier. If you plan to adapt the model to a narrow domain, that is a concrete differentiator.
Which handles multimodal inputs better?
Multimodal scores are 81 (Kimi K3) vs 70 (MiniMax M3), with modality coverage text/image versus text. Match the model to the input types your product actually receives.
What is the single-line recommendation?
Choose Kimi K3 for Long-document reading, Codebase analysis; choose MiniMax M3 for AI agents, Open source.