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Comparison · 3 models · Updated Nov 2, 2026

MiMo-V2-Pro vs Kimi K2 Instruct 0905 vs Grok 4.20 (Non-Reasoning)

Grok 4.20 (Non-Reasoning) comes out ahead, 52 to 42 and 38 on our weighted score, though Kimi K2 Instruct 0905 is 31% cheaper per token.

  1. Xiaomi

    MiMo-V2-Pro

    Released Mar 18, 2026

    42/100
    • ECI—
    • Price$1.00 / $3.00
    • Context1.05M
  2. Moonshot AI

    Kimi K2 Instruct 0905

    Released Sep 5, 2025

    38/100
    • ECI—
    • Price$0.60 / $2.50
    • Context262K
  3. Our pick

    xAI

    Grok 4.20 (Non-Reasoning)

    Released Mar 9, 2026

    52/100
    • ECI—
    • Price$1.25 / $2.50
    • Context1M
01 — Verdict

Grok 4.20 (Non-Reasoning) is our pick

Grok 4.20 (Non-Reasoning) is the better all-round choice, scoring 52/100 against MiMo-V2-Pro (42) and Kimi K2 Instruct 0905 (38). It leads on inputs & features. Kimi K2 Instruct 0905 wins on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

  • CapabilityNot enough dataNo independent benchmark covers every model here yet
  • Lowest priceKimi K2 Instruct 0905Kimi K2 Instruct 0905 $1.07 · MiMo-V2-Pro $1.50 · Grok 4.20 (Non-Reasoning) $1.56 per 1M tokens (3:1 blend)
  • Longest contextMiMo-V2-ProMiMo-V2-Pro 1,048,576 · Grok 4.20 (Non-Reasoning) 1,000,000 · Kimi K2 Instruct 0905 262,144 tokens
  • Widest inputsGrok 4.20 (Non-Reasoning)MiMo-V2-Pro: Text · Kimi K2 Instruct 0905: Text · Grok 4.20 (Non-Reasoning): Text, Images, PDFs
  • Self-hostingKimi K2 Instruct 0905Publishes downloadable weights (Modified MIT)
How the score is built
MeasureWeightMiMo-V2-ProKimi K2 Instruct 0905Grok 4.20 (Non-Reasoning)
Price50%404639
Inputs & features30%352570
Context window20%613760
Overall100%42/10038/10052/100

Left out because at least one model lacks the data: capability. The remaining weights were rescaled.

02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

MiMo-V2-Pro vs Kimi K2 Instruct 0905 vs Grok 4.20 (Non-Reasoning) specifications side by side
SpecificationMiMo-V2-ProXiaomiKimi K2 Instruct 0905Moonshot AIGrok 4.20 (Non-Reasoning)xAI
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
Input$1.00$0.60 (best)$1.25
Output$3.00$2.50 (best)$2.50 (best)
Cached input——$0.20
Blended (3:1)$1.50$1.07 (best)$1.56
Long-context rateSame rateSame rateOver 200K: $2.50 / $5.00
Price sourceMedian of 1 providersMedian of 12 providersOfficial xAI API
Limits
Context window1,048,576 tokens (best)262,144 tokens1,000,000 tokens
Max output131,072 tokens (best)98,304 tokens30,000 tokens
Inputs and features
TextYesYesYes
ImagesNoNoYes
PDFsNoNoYes
AudioNoNoNo
VideoNoNoNo
ReasoningYesNoNo
Tool callingYesYesYes
Structured outputNoNoYes
Availability
WeightsProprietaryOpenModified MITProprietary
API model ID——grok-4.20-0309-non-reasoning
API providers213 (best)13 (best)
ReleasedMar 18, 2026Sep 5, 2025Mar 9, 2026
Knowledge cutoffDec 2024——
03 — Cost

What would a month cost?

Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.

  • MiMo-V2-Pro$16.00
  • Kimi K2 Instruct 0905$11.00
  • Grok 4.20 (Non-Reasoning)$17.50
04 — Questions

Which should you choose?

Which is better: MiMo-V2-Pro, Kimi K2 Instruct 0905 or Grok 4.20 (Non-Reasoning)?

Grok 4.20 (Non-Reasoning) is the better all-round choice, scoring 52/100 against MiMo-V2-Pro (42) and Kimi K2 Instruct 0905 (38). It leads on inputs & features. Kimi K2 Instruct 0905 wins on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

Which is cheaper, MiMo-V2-Pro, Kimi K2 Instruct 0905 or Grok 4.20 (Non-Reasoning)?

Kimi K2 Instruct 0905 is cheaper at $0.60 input / $2.50 output per million tokens (median across 12 API providers). MiMo-V2-Pro costs $1.00 input / $3.00 output per million tokens (median across 1 API provider); Grok 4.20 (Non-Reasoning) costs $1.25 input / $2.50 output per million tokens (official xAI API price). At a typical mix of three input tokens to one output token, that is $1.07 per million tokens for Kimi K2 Instruct 0905 versus $1.50 for MiMo-V2-Pro (1.4× as much) and $1.56 for Grok 4.20 (Non-Reasoning) (1.5× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. MiMo-V2-Pro has not been scored yet, Kimi K2 Instruct 0905 has not been scored yet and Grok 4.20 (Non-Reasoning) has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for MiMo-V2-Pro, Kimi K2 Instruct 0905 and Grok 4.20 (Non-Reasoning) yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.

Which has the bigger context window?

MiMo-V2-Pro has the largest context window at 1,048,576 tokens, against 1,000,000 for Grok 4.20 (Non-Reasoning) and 262,144 for Kimi K2 Instruct 0905. Maximum output per response: MiMo-V2-Pro up to 131,072, Kimi K2 Instruct 0905 up to 98,304, Grok 4.20 (Non-Reasoning) up to 30,000 tokens.

Which can read images, PDFs, audio or video?

MiMo-V2-Pro accepts text; Kimi K2 Instruct 0905 accepts text; Grok 4.20 (Non-Reasoning) accepts text, images and PDFs. Grok 4.20 (Non-Reasoning) handles the widest range of inputs.

Are any of these open source?

Kimi K2 Instruct 0905 publishes its weights (Modified MIT) and can be self-hosted; MiMo-V2-Pro and Grok 4.20 (Non-Reasoning) is proprietary.

Which is newer?

MiMo-V2-Pro is the newest, released Mar 18, 2026. Grok 4.20 (Non-Reasoning) came out Mar 9, 2026; Kimi K2 Instruct 0905 came out Sep 5, 2025. Knowledge cutoff: MiMo-V2-Pro Dec 2024.

How do you decide the winner?

Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Nov 2, 2026.