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Comparison · 3 models · Updated Nov 2, 2026

Gemma 3 27B IT vs MiMo-V2-Flash 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. Google

    Gemma 3 27B IT

    Released Mar 12, 2025

    62/100
    • ECI129.9
    • Price$0.11 / $0.30
    • Context131K
  2. Xiaomi

    MiMo-V2-Flash

    Released Dec 16, 2025

    60/100
    • ECI—
    • Price$0.10 / $0.30
    • Context262K
  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 ITGemma 3 27B IT: Text, Images · MiMo-V2-Flash: Text · Rnj-1 Instruct: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightGemma 3 27B ITMiMo-V2-FlashRnj-1 Instruct
Price50%848585
Inputs & features30%503525
Context window20%25370
Overall100%62/10060/10050/100

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.

Gemma 3 27B IT vs MiMo-V2-Flash vs Rnj-1 Instruct specifications side by side
SpecificationGemma 3 27B ITGoogleMiMo-V2-FlashXiaomiRnj-1 InstructEssential AI
Capability
Capabilities Index (ECI)129.9——
ECI rank#137 of 165——
GPQA DiamondGraduate-level science questions47.7%——
OTIS Mock AIME 2024–2025Competition mathematics22.5%——
Price per million tokens
Input$0.11$0.10 (best)$0.15
Output$0.30$0.30$0.15 (best)
Cached input———
Blended (3:1)$0.157$0.15 (best)$0.15 (best)
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 16 providersMedian of 3 providersMedian of 1 providers
Limits
Context window131,072 tokens262,144 tokens (best)32,768 tokens
Max output131,072 tokens (best)65,536 tokens32,768 tokens
Inputs and features
TextYesYesYes
ImagesYesNoNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoYesNo
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsOpenOpenOpenApache 2.0
API model ID———
API providers17 (best)41
ReleasedMar 12, 2025Dec 16, 2025Dec 4, 2025
Knowledge cutoffAug 2024Dec 1, 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.

  • Gemma 3 27B IT$1.69
  • MiMo-V2-Flash$1.60
  • Rnj-1 Instruct$1.80
04 — Questions

Which should you choose?

Which is better: Gemma 3 27B IT, MiMo-V2-Flash 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, Gemma 3 27B IT, MiMo-V2-Flash 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. Gemma 3 27B IT has an ECI of 129.9, MiMo-V2-Flash has not been scored yet and Rnj-1 Instruct has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Gemma 3 27B IT, MiMo-V2-Flash 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: Gemma 3 27B IT up to 131,072, MiMo-V2-Flash up to 65,536, Rnj-1 Instruct up to 32,768 tokens.

Which can read images, PDFs, audio or video?

Gemma 3 27B IT accepts text and images; MiMo-V2-Flash accepts text; 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: Gemma 3 27B IT Aug 2024, MiMo-V2-Flash Dec 1, 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.