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Llama 4 Maverick vs Kimi K2.5

Meta AIMoonshot AIboth via one key, provider price + 3%

Llama 4 Maverick (Meta, released 2025-04-05) and Kimi K2.5 (Moonshot AI, released 2026-01-27) both take text and image input and return text, but they sit at opposite ends of the price-vs-capability curve. Maverick is a 17B-active-parameter MoE model built for scale and cheap throughput. Kimi K2.5 is nine months newer, priced higher, and posts sharply better scores across every Design Arena category the two share, plus a full agents benchmark suite Maverick isn't scored on at all.

Spec vs spec

SpecLlama 4 MaverickKimi K2.5
Context window1.0M262K
Max output16K
Input modalitiestext, imagetext, image
Output modalitiestexttext
Knowledge cutoffAug 31, 2024
ReleasedApr 5, 2025Jan 27, 2026
Reasoningoptional

Pricing

Per 1M tokens. Provider price plus the flat 3% fee — the sum is what you pay.

openkey.ai

meta-llama/llama-4-maverick

Input · 1M tokens

$0.150 + 3%$0.154

Output · 1M tokens

$0.600 + 3%$0.618

FEE — FLAT, EVERY MODEL3%

openkey.ai

moonshotai/kimi-k2.5

Input · 1M tokens

$0.375 + 3%$0.386

Output · 1M tokens

$2.02 + 3%$2.09

FEE — FLAT, EVERY MODEL3%

One workload, priced on both

10M input + 2M output tokens at each model's price, flat 3% fee included.

meta-llama/llama-4-maverickCheaper

$2.78

$2.70 provider + 3%

moonshotai/kimi-k2.5

$8.03

$7.80 provider + 3%

Benchmarks

Design Arena categories where both models have results. Higher Elo and lower rank win.

Llama 4 MaverickKimi K2.5
CategoryEloRankEloRank
3D976#911286#22
Code929#1021286#20
Data viz926#1001270#21
Game dev903#1031272#23
UI components955#941290#19
Websites914#1051291#16

Head-to-head preference voting. How we filter and rank

Pricing math

On OpenKey, Llama 4 Maverick costs $0.1545/M input and $0.618/M output tokens (provider price $0.15 / $0.60 x 1.03 for the flat 3% fee). Kimi K2.5 costs $0.38625/M input and $2.08575/M output (provider $0.375 / $2.025 x 1.03). Run a 10M-input / 2M-output workload and Maverick costs $2.70 total versus Kimi K2.5's $7.80 — Kimi K2.5 is roughly 2.9x more expensive for the same workload. Maverick's input price is 0.4x Kimi K2.5's, meaning Kimi K2.5 input tokens cost about 2.5x as much. If you're processing large batches of straightforward text, that gap compounds fast.

Coding and agent benchmarks

On Design Arena's model-vs-model categories, Kimi K2.5 beats Maverick everywhere both are scored: codecategories (1286 Elo, rank 20 vs Maverick's 929 Elo, rank 102), dataviz (1270 vs 926), gamedev (1272 vs 903), uicomponent (1290 vs 955), website (1291 vs 914), and 3d (1286 vs 976). Kimi K2.5 also has agent-arena scores Maverick lacks entirely: fullstack (1182 Elo, rank 14), web apps (1194, rank 15), Godot game dev (1254, rank 2), Android native (1132, rank 17), and mobile apps (1186, rank 20). Separately, Artificial Analysis puts Maverick's coding index at 16.3 and agentic index at just 1.3 — low numbers that line up with its weaker Design Arena ranks (mostly 90s-100s out of the field) versus Kimi K2.5's ranks mostly in the teens and 20s.

Context and long-document work

Maverick's 1,048,576-token context window is 4x Kimi K2.5's 262,144 tokens. For ingesting a full codebase, a long legal contract, or a multi-document research dump in one pass, Maverick has more headroom. Its max completion is capped at 16,384 tokens; Kimi K2.5 has no stated max-completion limit in this data. If your workload is dominated by huge inputs and short outputs — RAG-style summarization, log analysis, document Q&A — Maverick's context advantage plus its lower input price make it the practical default.

When to pick each

Pick Kimi K2.5 when the task is coding, UI/game/web generation, or anything resembling agentic multi-step work — the Design Arena gaps are large and consistent, not marginal. Pick Llama 4 Maverick when you're processing large volumes of text or images at low cost, need a very large context window, or the task doesn't require top-tier code generation. Kimi K2.5 also ships reasoning support (`reasoning` parameter, enabled by default, not mandatory) that Maverick's parameter list doesn't include at all — useful if you want the model to show its work on harder problems.

Which model for which job

Use casePickWhy
Full-stack app scaffoldingKimi K2.51182 Elo, rank 14 in Design Arena's fullstack agent category vs no score for Maverick
Bulk document summarizationLlama 4 Maverick1,048,576-token context (4x Kimi K2.5's 262,144) at $0.1545/M input
UI component generationKimi K2.51290 Elo, rank 19 vs Maverick's 955 Elo, rank 94
High-volume, cost-capped text jobsLlama 4 Maverick10M in / 2M out costs $2.70 vs Kimi K2.5's $7.80
Godot/game-dev agent tasksKimi K2.51254 Elo, rank 2 in the agents godotgamedev category — Maverick has no agent-arena score
Image-input tasks on a tight budgetLlama 4 Maverickboth support text+image input, but Maverick's input price is 0.4x Kimi K2.5's

Questions

How much cheaper is Llama 4 Maverick than Kimi K2.5?
For a 10M-input/2M-output workload, Maverick costs $2.70 on OpenKey versus $7.80 for Kimi K2.5 — Kimi K2.5 runs about 2.9x more expensive for the same token volume. The input-price ratio alone is 0.4, meaning Maverick's input tokens cost 40% of what Kimi K2.5's do.
Which model is better for coding?
Kimi K2.5, by a wide margin. It scores 1286 Elo (rank 20) on Design Arena's codecategories versus Maverick's 929 Elo (rank 102). Maverick's own Artificial Analysis coding index is 16.3, well below what its Design Arena ranks suggest is competitive territory.
Which has the larger context window?
Llama 4 Maverick, at 1,048,576 tokens versus Kimi K2.5's 262,144 tokens — a 4x ratio. Maverick's max completion output is capped at 16,384 tokens; Kimi K2.5 has no stated cap in the spec data.
Can I use both models through one API key?
Yes — both Llama 4 Maverick and Kimi K2.5 are available on OpenKey with a single API key, and pricing on both is the provider's list price plus a flat 3% fee (e.g. Maverick's $0.15/M provider input price becomes $0.1545/M on OpenKey).

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