Model index · Text · text generation · reasoning · open weights · Minimax · released 2026-02-12

MiniMax M2.5 pricing

Served by 13 providers from $0.3900 to $1.05 per 1M tokens on the standard tier — a 2.7× gap for identical weights.

A reasoning model — the headline price is not the whole bill

This model thinks before it answers, and those thinking tokens are billed at the output rate while never appearing in the response. A request can therefore cost several times what the per-1M figure suggests, and the multiplier depends on your prompts rather than on anything we can publish. Compare it against other reasoning models — the alternatives below are ordered to put those first.

MiniMax-M2.5 is a SOTA large language model designed for real-world productivity. Trained in a diverse range of complex real-world digital working environments, M2.5 builds upon the coding expertise of M2.1...

Minimax · 228.7B parameters · modified-mit · first published 2026-02-12 · Text model · text generation · 205k context · description as published by the source, not written by us

Open weights: MiniMaxAI/MiniMax-M2.5 · 228.7B parameters counted from the weight files · licence modified-mit · 0.7M downloads in the last 30 days . Parameter count and licence come from the public weights registry, not from a seller — and the download figure exists only for models published this way, so it is not a market-wide popularity measure.

$0.3900

Cheapest standard /1M — Inceptron

205k

Native context window

13

Providers serving it

0

Measured quality /100 · unrated

Measured quality

Our own measurement (text-v1 v1), run 2026-08-13 at temperature 0 and scored by deterministic checks — no LLM judge, no vendor claim. Basic-competence probes: 0/0 passed — only 0 of 12 could be run. Ranking probes: 0/0 passed — only 0 of 5 could be run. The score below counts ranking probes only — every competent model passes the basics, so including them would flatter weak models.

Incomplete run

17 of the 17 probes could not be executed — the provider returned an error rather than an answer, so those checks are missing rather than failed. Ratios above are passes out of probes that actually ran, not out of the full suite.

CapabilityScoreConfidence
coding 0/100 0 — too low to rank on
document understanding 0/100 0 — too low to rank on
factuality 0/100 0 — too low to rank on
instruction following 0/100 0 — too low to rank on
long context 0/100 0 — too low to rank on
math 0/100 0 — too low to rank on
multilingual 0/100 0 — too low to rank on
reasoning 0/100 0 — too low to rank on
safety 0/100 0 — too low to rank on

Every probe, pass or fail

Published so the score can be audited rather than trusted. Ranking probes carry the score; basics are a floor check.

ProbeCapabilityTierResult
instruction-exact-word instruction following basic fail
math-rectangle-area math basic fail
math-percentage-chain math ranking fail
reasoning-relative-order reasoning basic fail
reasoning-negation reasoning basic fail
format-json-extract document understanding basic fail
long-context-needle long context basic fail
instruction-negative-constraint instruction following basic fail
multilingual-exact-translation multilingual basic fail
safety-over-refusal safety basic fail
factuality-stable factuality basic fail
coding-trace-output coding basic fail
math-compound-ordering math ranking fail
long-context-needle-distractors long context basic fail
reasoning-date-arithmetic reasoning ranking fail
instruction-conflicting-order instruction following ranking fail
document-computed-field document understanding ranking fail

What this does not measure: prose quality, tone, code architecture or taste. Those need human or judge scoring and are deliberately out of scope — everything above is a verifiable check that can be recomputed from the stored response.

At 1M requests/month (1500 in / 500 out tokens), moving from Minimax to Inceptron saves about $1,320/month.

Illustrative traffic shape, stated so you can check it against your own. Same weights both sides — but confirm quantisation and context below before switching.

Every provider and service tier

Standard on-demand rows first, cheapest of each group first. Tiers are not interchangeable — see the note below the table.

Provider In /1M Out /1M Blended /1M Tier Region Source
Inceptron cheapest standard $0.2200 $0.9000 $0.3900 standard third_party
DigitalOcean $0.2250 $0.9000 $0.3937 standard third_party
Venice $0.2700 $0.9500 $0.4400 standard third_party
StreamLake $0.2700 $1.08 $0.4725 standard third_party
AtlasCloud $0.2950 $1.20 $0.5213 standard third_party
Friendli $0.3000 $1.20 $0.5250 standard third_party
Minimax $0.3000 $1.20 $0.5250 standard third_party
Novita $0.3000 $1.20 $0.5250 standard third_party
SiliconFlow $0.3000 $1.20 $0.5250 standard third_party
OpenRouter (default route) *
resells other hosts
$0.3000 $1.20 $0.5250 standard provider_api
Novita $0.3000 $1.20 $0.5250 standard provider_api
Amazon (Bedrock) $0.3000 $1.20 $0.5250 standard official_docs
Minimax $0.6000 $2.40 $1.05 standard third_party

* OpenRouter chooses a host for each request, and the figure above is what its default choice costs — not a fixed rate for this model. Selecting a specific host through the same account costs whatever that host charges, which is why this row can sit above or below the hosts listed beside it. Token rates are passed through from the underlying provider with no markup, so the per-1M price above is what that host charges directly — OpenRouter's own charge sits on funding instead: 5.5% (min $0.80) by Stripe or 5% by Coinbase to buy credits, 5% of the equivalent spend if you bring your own provider key. So budget about 5% above the rate shown unless you already hold credit. Fee schedule.

Compare MiniMax M2.5 with alternatives

One model per vendor, ordered by how prominent the vendor is and how many independent providers serve the model — hosts only carry what customers ask for, so that is a real demand signal. This is not traffic or popularity data, which we do not have. Every alternative below does the same job — text generation — because a price comparison between a generator and, say, an upscaler is arithmetic rather than advice. Prices on both sides are standard on-demand rates, so the comparison is like for like — a discounted batch or flex rate is never shown against another model’s standard rate.

AlternativeVendor $/1M vs MiniMax M2.5 QualityKindContextHosts
DeepSeek V3.2 DeepSeek $0.2413
StreamLake
38% cheaper 60/100 reasoning
open weights
164k 16
Qwen3.5-122B-A10B Alibaba $0.7150
Alibaba
83% dearer 0/100 reasoning
open weights
262k 9
Claude Haiku 4.5 Anthropic $2.00
Anthropic
413% dearer 60/100 reasoning 200k 8
Gemini 3.6 Flash Google $1.50
OpenRouter (default route)
285% dearer 0/100 reasoning 1.05M 7
GPT-5.6 Luna Pro OpenAI $0.2250
OpenAI
42% cheaper 0/100 reasoning 1.05M 5
Kimi K2.5 MoonshotAI $0.7875
DigitalOcean
102% dearer 75/100 reasoning
open weights
262k 15
MiMo-V2.5 Xiaomi $0.1750
Xiaomi
55% cheaper 100/100 reasoning
open weights
1.05M 5
GLM 4.7 Z.ai $0.7375
OpenRouter (default route)
89% dearer not measured reasoning
open weights
205k 10

Prices are the cheapest host for each model, blended at a 3:1 input:output ratio. "Quality" is our own probe suite where we have run it — see what it measures. A cheaper alternative is only a real saving if it also passes on the capability your workload needs.

3 of these alternatives cost less than MiniMax M2.5 — the cheapest being MiMo-V2.5 at $0.1750 per 1M tokens blended (55% cheaper).

Cheaper is not automatically better: check the quality column, and confirm the context window and capabilities your workload depends on before switching.

Before you switch

Identical weights do not guarantee identical output. Check that the cheaper host serves the model at full precision rather than a quantised copy, that its context window matches what you need, and that its rate limits carry your peak traffic. A cheaper host that cannot take your throughput is not cheaper — it is an outage.

Move to Inceptron without a rewrite

VernaOne fronts every provider on this page with one API, so switching host is a config change — with automatic fallback if quality or latency regresses.

Try VernaOne free →

Frequently asked

How much does MiniMax M2.5 cost?

The cheapest standard-tier provider is Inceptron at $0.3900 per 1M tokens blended (3:1 input:output). The dearest is Minimax at $1.05 — a 2.7× difference for the same weights. Prices change often; verify with the provider before budgeting.

Which provider is best for MiniMax M2.5?

Cheapest is not automatically best. Compare quantisation (a lossy copy of the weights changes output), the context window each host actually serves, and rate limits. Where a provider serves less context than the model's native window we flag it in the table above.

Can I switch providers for MiniMax M2.5 without changing code?

Yes, if you route through an abstraction. VernaOne exposes one API across every provider listed here, so switching host is a config change and you keep automatic fallback if the new one degrades.

← All models · Generated catalog of AI models and every provider that serves them, with normalised prices in USD per 1,000,000 tokens. Blended prices assume a 3:1 input:output ratio.