Skip to main content
AI Choice Engine

Model comparison

DeepSeek V4 Pro vs Xiaomi MiMo-V2.6-Pro

DeepSeek against Xiaomi, compared on context, price, and verified benchmark results.

Catalog record checked September 26, 2026Individual provider fields may changeEvidence confidence: High — see receipts below

DeepSeek

DeepSeek V4 Pro

Frontier · Open weights

vs

Xiaomi

Xiaomi MiMo-V2.6-Pro

Frontier · Open weights

AI model capability comparison
SpecificationDeepSeek V4 ProXiaomi MiMo-V2.6-Pro
ProviderDeepSeekXiaomi
TierFrontierFrontier
Context window1MWinner: 1.05M
Max output384KNot verifiedUnverified
Input / 1M tokens$1.32Winner: $0.435
Output / 1M tokens$3.96Winner: $0.87
WeightsOpenOpen
Parameters1.6T total / 49B active (MoE)1.02T total / 42B active (MoE)
Reasoning levelslow, high, maxNot verifiedUnverified
Modalitiestexttext, image, video, audio
LicenseMITMIT
API model iddeepseek-v4-promimo-v2.6-pro
ReleasedApril 24, 2026September 21, 2026
Artificial Analysis Intelligence Index [max] (2026-09-26)36Not verifiedUnverified
Artificial Analysis Intelligence Index (2026-09-26)Not verifiedUnverified46.3
SWE-bench Verified (2026-04-24)80.6Not verifiedUnverified
GPQA Diamond (2026-04-24)90.1Not verifiedUnverified
Humanity's Last Exam (2026-04-24)48.2Not verifiedUnverified
MMLU-Pro (2026-04-24)87.5Not verifiedUnverified
DeepSWE 1.1 (2026-09-21)Not verifiedUnverified71.9
Terminal-Bench 2.1 (2026-09-21)Not verifiedUnverified89.9

Prices are USD per million tokens at standard rates, excluding batch and caching discounts. Bold indicates the better figure where one is objectively better. Values we could not confirm from the provider are shown as “Not verified” rather than estimated.

Benchmark receipts

Where each score comes from, and how far it can be compared across models.

  • 2026-09-26
    Artificial Analysis

    Composite index blending reasoning, knowledge, and coding evals into one 0–100 score.

    Comparable with caveatOnly same-version scores are comparable. v4.3.2 was rebaselined (the top score fell from 66 on v4.1.1 to ~58), so v4.1.1 figures must not be compared with v4.3.2 figures — check measuredAt.

  • 2026-09-21
    Xiaomi MiMo-V2.6 announcement (vendor)

    Agentic software engineering: pass@1 on real repo tasks with reported cost per completed task.

    Directly comparable

  • 2026-04-24
    DeepSeek V4 Pro HF model card (vendor, Think Max, exact match)

    Real GitHub issue resolution: does the model's patch pass the hidden tests.

    Comparable with caveatPost-audit vendor claims and pre-audit scores sit on different task trust levels; scaffolding (agent harness, compute budget) also dominates results. Never aggregate across scaffolds.

Pricing tiers

DeepSeek V4 Pro: Official peak rates $1.32/$3.96 per MTok; off-peak $0.66/$1.98 (cache-miss). Cache hit $0.044 peak / $0.022 off-peak. Peak hours are weekdays 01:00–04:00 and 06:00–10:00 UTC. Open weights (MIT). 1.6T/49B active MoE.

Xiaomi MiMo-V2.6-Pro: $0.435/$0.87 per MTok (cache hit $0.0036; cache writes free for a limited time) — unchanged from V2.5-Pro. UltraSpeed mode (mimo-v2.6-pro-ultraspeed) costs $4.35/$8.70. Open weights (MIT) as MiMo-V2.6-Pro-RL.

FrontierOpen weightsRecord checked September 26, 2026

DeepSeek V4 Pro

DeepSeek V4 Pro is DeepSeek's large open-weight (MIT) MoE with a 1M-token context — DeepSeek says the cheaper V4.1-Flash now beats it.

Best for

  • Cost-sensitive hosted agents
  • Open-weight deployments
  • High-volume coding

Watch out

On 2026-09-10 DeepSeek said it is phasing out V4-Pro (it later reversed the 2026-09-14 re-route and still serves it); plan new work on V4.1-Flash. Self-hosting needs datacentre VRAM.

FrontierOpen weightsRecord checked September 26, 2026

Xiaomi MiMo-V2.6-Pro

MiMo-V2.6-Pro is Xiaomi's open-weight (MIT) 1.02T MoE with omni-modal input and a 1M context — the top open-weight model on the Artificial Analysis index at under $1 per million output tokens.

Best for

  • Open-weight frontier work
  • Omni-modal input
  • Cheap long-context API

Watch out

Max output is not verified; vendor benchmark claims (DeepSWE 71.9) are not yet independently reproduced.

When the cheaper one wins

Xiaomi MiMo-V2.6-Pro is cheaper on output at $0.87 per million tokens against $3.96 for DeepSeek V4 Pro — about 4.6×. Use the cheaper tier for classification, extraction, summarisation, and any task where the expensive model’s extra score does not change the accepted output. The expensive one only pays if your hardest task actually fails on the cheap tier. These are standard-tier API rates, excluding batch and cache discounts.

Run the model picker

Evidence confidence: High

How strong and complete the evidence behind this comparison is — not a prediction of which model is better.

  • Pricing verified on both sides — Input and output rates are verified for both models.
  • 3/5 core specs verified on both sides — Not published for at least one side: max output, reasoning levels.
  • 1 shared named benchmark with differing scores — Measured on: Artificial Analysis Intelligence Index.
  • Verified within the last 90 days — Newest catalog check was 2 days ago.
  • Both models carry source citations — Each side has at least two catalog sources on record.

Source receipts

Each catalog figure was checked against the provider or an independent second source on the date shown.

Related comparisons

Diving deeper on one model? DeepSeek V4 Pro · Xiaomi MiMo-V2.6-Pro

Common questions

DeepSeek V4 Pro vs Xiaomi MiMo-V2.6-Pro

Answered from the verified figures on this page rather than general guidance.

Is DeepSeek V4 Pro or Xiaomi MiMo-V2.6-Pro cheaper for input?
Xiaomi MiMo-V2.6-Pro is cheaper at $0.435 per million input tokens, against $1.32 for DeepSeek V4 Pro — roughly 3.0× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; DeepSeek V4 Pro has tiered pricing: Official peak rates $1.32/$3.96 per MTok; off-peak $0.66/$1.98 (cache-miss). Cache hit $0.044 peak / $0.022 off-peak. Peak hours are weekdays 01:00–04:00 and 06:00–10:00 UTC. Open weights (MIT). 1.6T/49B active MoE. Xiaomi MiMo-V2.6-Pro has tiered pricing: $0.435/$0.87 per MTok (cache hit $0.0036; cache writes free for a limited time) — unchanged from V2.5-Pro. UltraSpeed mode (mimo-v2.6-pro-ultraspeed) costs $4.35/$8.70. Open weights (MIT) as MiMo-V2.6-Pro-RL.
Is DeepSeek V4 Pro or Xiaomi MiMo-V2.6-Pro cheaper for output?
Xiaomi MiMo-V2.6-Pro is cheaper at $0.87 per million output tokens, against $3.96 for DeepSeek V4 Pro — roughly 4.6× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; DeepSeek V4 Pro has tiered pricing: Official peak rates $1.32/$3.96 per MTok; off-peak $0.66/$1.98 (cache-miss). Cache hit $0.044 peak / $0.022 off-peak. Peak hours are weekdays 01:00–04:00 and 06:00–10:00 UTC. Open weights (MIT). 1.6T/49B active MoE. Xiaomi MiMo-V2.6-Pro has tiered pricing: $0.435/$0.87 per MTok (cache hit $0.0036; cache writes free for a limited time) — unchanged from V2.5-Pro. UltraSpeed mode (mimo-v2.6-pro-ultraspeed) costs $4.35/$8.70. Open weights (MIT) as MiMo-V2.6-Pro-RL.
Which has the larger context window, DeepSeek V4 Pro or Xiaomi MiMo-V2.6-Pro?
Xiaomi MiMo-V2.6-Pro accepts 1.05M tokens against 1M for DeepSeek V4 Pro. This only matters if you routinely send very long documents or large codebases.
Should I use DeepSeek V4 Pro or Xiaomi MiMo-V2.6-Pro?
Both sit in the frontier tier, so the choice usually comes down to price and context rather than capability. DeepSeek V4 Pro suits cost-sensitive hosted agents; Xiaomi MiMo-V2.6-Pro suits open-weight frontier work.

Next step

Choosing between them

The verified figures that separate this pair, computed from the catalog rather than restated boilerplate.

  • Input price: Xiaomi MiMo-V2.6-Pro costs $0.435 per 1M tokens versus $1.32 for DeepSeek V4 Pro — a 3x difference at the headline tier.
  • Context: Xiaomi MiMo-V2.6-Pro takes 1.05M against 1M for DeepSeek V4 Pro — only decisive if your prompts approach the smaller window.
Run the model pickerEstimate stack costAll model comparisons

Choosing a harness rather than a model — Cursor, Copilot, Claude Code, Windsurf, or Lovable? Compare agentic harnesses · Latest releases.