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Comparison · 3 models · Updated Oct 4, 2026

MiniMax-M2.7-highspeed vs Trinity Large Thinking vs Qwen3.5 122B-A10B

Qwen3.5 122B-A10B comes out ahead, 58 to 55 and 41 on our weighted score, though Trinity Large Thinking is 2.8× cheaper per token.

  1. MiniMax

    MiniMax-M2.7-highspeed

    Released Mar 18, 2026

    41/100
    • ECI—
    • Price$0.60 / $2.40
    • Context205K
    Full specs Remove MiniMax-M2.7-highspeed

  2. Arcee AI

    Trinity Large Thinking

    Released Apr 1, 2026Beta

    55/100
    • ECI—
    • Price$0.25 / $0.80
    • Context524K
    Full specs Remove Trinity Large Thinking
  3. Our pick

    Alibaba (Qwen)

    Qwen3.5 122B-A10B

    Released Feb 23, 2026

    58/100
    • ECI—
    • Price$0.40 / $3.20
    • Context262K
    Full specs Remove Qwen3.5 122B-A10B
01 — Verdict

Qwen3.5 122B-A10B is our pick

Qwen3.5 122B-A10B is the better all-round choice, scoring 58/100 against Trinity Large Thinking (55) and MiniMax-M2.7-highspeed (41). It leads on inputs & features. Trinity Large Thinking wins on price and context window. 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 priceTrinity Large ThinkingTrinity Large Thinking $0.388 · MiniMax-M2.7-highspeed $1.05 · Qwen3.5 122B-A10B $1.10 per 1M tokens (3:1 blend)
  • Longest contextTrinity Large ThinkingTrinity Large Thinking 524,288 · Qwen3.5 122B-A10B 262,144 · MiniMax-M2.7-highspeed 204,800 tokens
  • Widest inputsQwen3.5 122B-A10BMiniMax-M2.7-highspeed: Text · Trinity Large Thinking: Text · Qwen3.5 122B-A10B: Text, Images, Audio, Video
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightMiniMax-M2.7-highspeedTrinity Large ThinkingQwen3.5 122B-A10B
Price50%496948
Inputs & features30%353590
Context window20%324937
Overall100%41/10055/10058/100

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.

MiniMax-M2.7-highspeed vs Trinity Large Thinking vs Qwen3.5 122B-A10B specifications side by side
SpecificationMiniMax-M2.7-highspeedMiniMaxTrinity Large ThinkingArcee AIQwen3.5 122B-A10BAlibaba (Qwen)
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
Input$0.60$0.25 (best)$0.40
Output$2.40$0.80 (best)$3.20
Cached input$0.06$0.06—
Blended (3:1)$1.05$0.388 (best)$1.10
Long-context rateSame rateSame rateSame rate
Price sourceOfficial MiniMax (minimax.io) APIOfficial Arcee APIOfficial Alibaba API
Limits
Context window204,800 tokens524,288 tokens (best)262,144 tokens
Max output131,072 tokens262,144 tokens (best)65,536 tokens
Inputs and features
TextYesYesYes
ImagesNoNoYes
PDFsNoNoNo
AudioNoNoYes
VideoNoNoYes
ReasoningYesYesYes
Tool callingYesYesYes
Structured outputNoNoYes
Availability
WeightsOpenOpenOpenMDW-1.1Open
API model IDMiniMax-M2.7-highspeedtrinity-large-thinkingqwen3.5-122b-a10b
API providers14619 (best)
ReleasedMar 18, 2026Apr 1, 2026Feb 23, 2026
Knowledge cutoff———
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.

  • MiniMax-M2.7-highspeed$10.80
  • Trinity Large Thinking$4.10
  • Qwen3.5 122B-A10B$10.40
04 — Questions

Which should you choose?

Which is better: MiniMax-M2.7-highspeed, Trinity Large Thinking or Qwen3.5 122B-A10B?

Qwen3.5 122B-A10B is the better all-round choice, scoring 58/100 against Trinity Large Thinking (55) and MiniMax-M2.7-highspeed (41). It leads on inputs & features. Trinity Large Thinking wins on price and context window. 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, MiniMax-M2.7-highspeed, Trinity Large Thinking or Qwen3.5 122B-A10B?

Trinity Large Thinking is cheaper at $0.25 input / $0.80 output per million tokens (official Arcee API price). MiniMax-M2.7-highspeed costs $0.60 input / $2.40 output per million tokens (official MiniMax (minimax.io) API price); Qwen3.5 122B-A10B costs $0.40 input / $3.20 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.388 per million tokens for Trinity Large Thinking versus $1.05 for MiniMax-M2.7-highspeed (2.7× as much) and $1.10 for Qwen3.5 122B-A10B (2.8× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. MiniMax-M2.7-highspeed has not been scored yet, Trinity Large Thinking has not been scored yet and Qwen3.5 122B-A10B has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for MiniMax-M2.7-highspeed, Trinity Large Thinking and Qwen3.5 122B-A10B 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?

Trinity Large Thinking has the largest context window at 524,288 tokens, against 262,144 for Qwen3.5 122B-A10B and 204,800 for MiniMax-M2.7-highspeed. Maximum output per response: MiniMax-M2.7-highspeed up to 131,072, Trinity Large Thinking up to 262,144, Qwen3.5 122B-A10B up to 65,536 tokens.

Which can read images, PDFs, audio or video?

MiniMax-M2.7-highspeed accepts text; Trinity Large Thinking accepts text; Qwen3.5 122B-A10B accepts text, images, audio and video. Qwen3.5 122B-A10B handles the widest range of inputs.

Are any of these open source?

Yes, all three publish their weights (OpenMDW-1.1), so you can self-host them.

Which is newer?

Trinity Large Thinking is the newest, released Apr 1, 2026. MiniMax-M2.7-highspeed came out Mar 18, 2026; Qwen3.5 122B-A10B came out Feb 23, 2026.

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 Oct 4, 2026.

05 — Keep comparing

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