API cost decision in 10 seconds

Kimi K2.5 vs Kimi K2 0711

Pick Kimi K2.5 when budget and context both matter.

Page updated: 2026-05-26T15:08:08Z Data confirmed: 2026-05-26T19:08:13Z Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick Kimi K2.5 when budget and context both matter.

On the standard 1M input plus 500K output workload, Kimi K2.5 is estimated at $1.35 vs $1.72 for Kimi K2 0711, saving $0.37 (21.5% lower).

Cost-first pickKimi K2.5

Context-first pickKimi K2.5

Sample savings$0.3721.5%

10x traffic gap$3.7

Kimi K2.5 is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $3.7. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Kimi K2.5 stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shape	Token mix	Better pick	Kimi K2.5	Kimi K2 0711
Input-heavy / RAG	5M input + 500K output	Kimi K2.5	$2.95	$4
Balanced workload	1M input + 1M output	Kimi K2.5	$2.3	$2.87
Output-heavy chatbot	1M input + 5M output	Kimi K2.5	$9.9	$12.07

Cheaper input Kimi K2.5 $0.4 vs $0.57 / 1M

Kimi K2.5 is $0.17 cheaper per 1M input tokens (29.8% lower; 1.42x difference).

Cheaper output Kimi K2.5 $1.9 vs $2.3 / 1M

Kimi K2.5 is $0.4 cheaper per 1M output tokens (17.4% lower; 1.21x difference).

Larger context Kimi K2.5 262.14K vs 131.07K

Kimi K2.5 has 131.07K more context (2x larger).

Sample workload Kimi K2.5 $1.35 vs $1.72

Kimi K2.5 is $0.37 cheaper on the standard workload (21.5% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.

Monthly input tokens Monthly output tokens

Kimi K2.5 Calculating… Estimated API cost

Kimi K2 0711 Calculating… Estimated API cost

Cheaper for this workload Calculating… Difference: calculating…

This estimate uses normalized public API pricing per 1M tokens. It is a planning aid, not a billing quote. Verify provider pricing, limits, and terms before production use.

Quick Decision

Verdict

Kimi K2.5 has the lower input price; Kimi K2.5 has the lower output price; Kimi K2.5 offers the larger context window. For the 1M input plus 500K output sample, Kimi K2.5 is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $1.35 for Kimi K2.5 and $1.72 for Kimi K2 0711.

Best Fit

Choose Kimi K2.5 when you care most about lower input-token price, lower output-token price, and larger context window.

Choose Kimi K2 0711 when its provider, model quality, latency, or availability is more important than the numeric price/context winner.

Decision Notes

On the standard 1M input plus 500K output workload, Kimi K2.5 is estimated at $1.35 vs $1.72 for Kimi K2 0711, saving $0.37 (21.5% lower).
Kimi K2.5 is $0.37 cheaper on the standard workload (21.5% lower).
Kimi K2.5 is $0.17 cheaper per 1M input tokens (29.8% lower; 1.42x difference).
Kimi K2.5 is $0.4 cheaper per 1M output tokens (17.4% lower; 1.21x difference).
Kimi K2.5 has 131.07K more context (2x larger).

Head-to-Head Specs

Feature	Kimi K2.5 (MoonshotAI)	Kimi K2 0711 (MoonshotAI)
Input Price prompt tokens per 1M	$0.4	$0.57
Completion Price per 1M tokens	$1.9	$2.3
Sample Workload Cost 1M input + 500K output	$1.35	$1.72
Context Window	262.14K	131.07K
Release Date	2026-01-27	2025-07-11
Popularity	#36	#140

Use-Case Decision Matrix

Use case	Better pick	Why
Budget-constrained production	Kimi K2.5	On the standard 1M input plus 500K output workload, Kimi K2.5 is estimated at $1.35 vs $1.72 for Kimi K2 0711, saving $0.37 (21.5% lower).
High-volume input processing	Kimi K2.5	Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbots	Kimi K2.5	Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document work	Kimi K2.5	A larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Same-provider lower-cost swaps

No lower-cost same-provider swap is currently tracked for this pair.

Larger context near this budget

Llama 4 Scout offers 10M context with $0.23 sample workload cost.
Owl Alpha offers 1.05M context with $0 sample workload cost.
DeepSeek V4 Flash offers 1.05M context with $0.2 sample workload cost.
DeepSeek V4 Pro offers 1.05M context with $0.87 sample workload cost.

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Cheaper alternatives

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Larger context alternatives

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Provider catalogs

Compare models within provider hubs before choosing a final API vendor.

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MoonshotAI catalog

Review all tracked MoonshotAI models before deciding whether this matchup is the right shortlist.

Open MoonshotAI models

Kimi K2.5

Kimi K2.5 is Moonshot AI's native multimodal model, delivering state-of-the-art visual coding capability and a self-directed agent swarm paradigm. Built on Kimi K2 with continued pretraining over approximately 15T mixed...

Kimi K2 0711

Kimi K2 Instruct is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trillion total parameters with 32 billion active per forward pass. It is optimized for...