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Comparison · 3 models · Updated Nov 2, 2026

MiMo-V2-Flash vs Gemma 3 27B IT vs Rnj-1 Instruct

Too close to call on our weighted score (Gemma 3 27B IT 62, MiMo-V2-Flash 60, Rnj-1 Instruct 50). The right pick depends on what you value most.

  1. Xiaomi

    MiMo-V2-Flash

    Released Dec 16, 2025

    60/100
    • ECI—
    • Price$0.10 / $0.30
    • Context262K
  2. Google

    Gemma 3 27B IT

    Released Mar 12, 2025

    62/100
    • ECI129.9
    • Price$0.11 / $0.30
    • Context131K
  3. Essential AI

    Rnj-1 Instruct

    Released Dec 4, 2025

    50/100
    • ECI—
    • Price$0.15 / $0.15
    • Context33K
01 — Verdict

Too close to call

It is close. Our weighted score puts them within 2 points (Gemma 3 27B IT 62/100, MiMo-V2-Flash 60/100, Rnj-1 Instruct 50/100), so choose by what matters most for your work: MiMo-V2-Flash on price and MiMo-V2-Flash for long inputs. 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 priceMiMo-V2-Flash and Rnj-1 InstructMiMo-V2-Flash $0.15 · Rnj-1 Instruct $0.15 · Gemma 3 27B IT $0.157 per 1M tokens (3:1 blend)
  • Longest contextMiMo-V2-FlashMiMo-V2-Flash 262,144 · Gemma 3 27B IT 131,072 · Rnj-1 Instruct 32,768 tokens
  • Widest inputsGemma 3 27B ITMiMo-V2-Flash: Text · Gemma 3 27B IT: Text, Images · Rnj-1 Instruct: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightMiMo-V2-FlashGemma 3 27B ITRnj-1 Instruct
Price50%858485
Inputs & features30%355025
Context window20%37250
Overall100%60/10062/10050/100

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-Flash vs Gemma 3 27B IT vs Rnj-1 Instruct specifications side by side
SpecificationMiMo-V2-FlashXiaomiGemma 3 27B ITGoogleRnj-1 InstructEssential AI
Capability
Capabilities Index (ECI)—129.9—
ECI rank—#137 of 165—
GPQA DiamondGraduate-level science questions—47.7%—
OTIS Mock AIME 2024–2025Competition mathematics—22.5%—
Price per million tokens
Input$0.10 (best)$0.11$0.15
Output$0.30$0.30$0.15 (best)
Cached input———
Blended (3:1)$0.15 (best)$0.157$0.15 (best)
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 3 providersMedian of 16 providersMedian of 1 providers
Limits
Context window262,144 tokens (best)131,072 tokens32,768 tokens
Max output65,536 tokens131,072 tokens (best)32,768 tokens
Inputs and features
TextYesYesYes
ImagesNoYesNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningYesNoNo
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsOpenOpenOpenApache 2.0
API model ID———
API providers417 (best)1
ReleasedDec 16, 2025Mar 12, 2025Dec 4, 2025
Knowledge cutoffDec 1, 2024Aug 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-Flash$1.60
  • Gemma 3 27B IT$1.69
  • Rnj-1 Instruct$1.80
04 — Questions

Which should you choose?

Which is better: MiMo-V2-Flash, Gemma 3 27B IT or Rnj-1 Instruct?

It is close. Our weighted score puts them within 2 points (Gemma 3 27B IT 62/100, MiMo-V2-Flash 60/100, Rnj-1 Instruct 50/100), so choose by what matters most for your work: MiMo-V2-Flash on price and MiMo-V2-Flash for long inputs. 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-Flash, Gemma 3 27B IT or Rnj-1 Instruct?

MiMo-V2-Flash is cheaper at $0.10 input / $0.30 output per million tokens (median across 3 API providers). Rnj-1 Instruct costs $0.15 input / $0.15 output per million tokens (median across 1 API provider); Gemma 3 27B IT costs $0.11 input / $0.30 output per million tokens (median across 16 API providers). At a typical mix of three input tokens to one output token, that is $0.15 per million tokens for MiMo-V2-Flash versus $0.15 for Rnj-1 Instruct (1× as much) and $0.157 for Gemma 3 27B IT (1× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. MiMo-V2-Flash has not been scored yet, Gemma 3 27B IT has an ECI of 129.9 and Rnj-1 Instruct has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for MiMo-V2-Flash, Gemma 3 27B IT and Rnj-1 Instruct 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-Flash has the largest context window at 262,144 tokens, against 131,072 for Gemma 3 27B IT and 32,768 for Rnj-1 Instruct. Maximum output per response: MiMo-V2-Flash up to 65,536, Gemma 3 27B IT up to 131,072, Rnj-1 Instruct up to 32,768 tokens.

Which can read images, PDFs, audio or video?

MiMo-V2-Flash accepts text; Gemma 3 27B IT accepts text and images; Rnj-1 Instruct accepts text. Gemma 3 27B IT handles the widest range of inputs.

Are any of these open source?

Yes, all three publish their weights (Apache 2.0), so you can self-host them.

Which is newer?

MiMo-V2-Flash is the newest, released Dec 16, 2025. Rnj-1 Instruct came out Dec 4, 2025; Gemma 3 27B IT came out Mar 12, 2025. Knowledge cutoff: MiMo-V2-Flash Dec 1, 2024, Gemma 3 27B IT Aug 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.