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Comparison · 2 models · Updated Nov 2, 2026

Qwen3.5 9B Base vs Trinity Large Thinking

Trinity Large Thinking comes out ahead, 53 to 50 on our weighted score, and it is the cheaper option too.

  1. Alibaba (Qwen)

    Qwen3.5 9B Base

    Released Feb 26, 2026

    50/100
    • ECI—
    • Price$0.30 / $0.807
    • Context262K
    Full specs Remove Qwen3.5 9B Base
  2. Our pick

    Arcee AI

    Trinity Large Thinking

    Released Apr 1, 2026Beta

    53/100
    • ECI—
    • Price$0.25 / $0.80
    • Context524K
    Full specs Remove Trinity Large Thinking

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Trinity Large Thinking is our pick

Trinity Large Thinking is the better all-round choice, scoring 53/100 against Qwen3.5 9B Base (50). It leads 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 · Qwen3.5 9B Base $0.427 per 1M tokens (3:1 blend)
  • Longest contextTrinity Large ThinkingTrinity Large Thinking 524,288 · Qwen3.5 9B Base 262,144 tokens
  • Widest inputsQwen3.5 9B BaseQwen3.5 9B Base: Text, Images, Video · Trinity Large Thinking: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightQwen3.5 9B BaseTrinity Large Thinking
Price50%6566
Inputs & features30%3535
Context window20%3749
Overall100%50/10053/100

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.

Qwen3.5 9B Base vs Trinity Large Thinking specifications side by side
SpecificationQwen3.5 9B BaseAlibaba (Qwen)Trinity Large ThinkingArcee AI
Capability
Capabilities Index (ECI)——
ECI rank——
Price per million tokens
Input$0.30$0.25 (best)
Output$0.807$0.80 (best)
Cached input—$0.06
Blended (3:1)$0.427$0.388 (best)
Long-context rateSame rateSame rate
Price sourceMedian of 1 providersOfficial Arcee API
Limits
Context window262,144 tokens524,288 tokens (best)
Max output65,536 tokens262,144 tokens (best)
Inputs and features
TextYesYes
ImagesYesNo
PDFsNoNo
AudioNoNo
VideoYesNo
ReasoningNoYes
Tool callingNoYes
Structured outputNoNo
Availability
WeightsOpenApache-2.0OpenOpenMDW-1.1
API model ID—trinity-large-thinking
API providers13 (best)
ReleasedFeb 26, 2026Apr 1, 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.

  • Qwen3.5 9B Base$4.61
  • Trinity Large Thinking$4.10
04 — Questions

Which should you choose?

Which is better: Qwen3.5 9B Base or Trinity Large Thinking?

Trinity Large Thinking is the better all-round choice, scoring 53/100 against Qwen3.5 9B Base (50). It leads 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, Qwen3.5 9B Base or Trinity Large Thinking?

Trinity Large Thinking is cheaper at $0.25 input / $0.80 output per million tokens (official Arcee API price). Qwen3.5 9B Base costs $0.30 input / $0.807 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $0.388 per million tokens for Trinity Large Thinking versus $0.427 for Qwen3.5 9B Base (1.1× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers both models yet. Qwen3.5 9B Base has not been scored yet and Trinity Large Thinking has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen3.5 9B Base and Trinity Large Thinking yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Qwen3.5 9B Base does not support tool calling, which most coding agents need.

Which has the bigger context window?

Trinity Large Thinking has the largest context window at 524,288 tokens, against 262,144 for Qwen3.5 9B Base. Maximum output per response: Qwen3.5 9B Base up to 65,536, Trinity Large Thinking up to 262,144 tokens.

Which can read images, PDFs, audio or video?

Qwen3.5 9B Base accepts text, images and video; Trinity Large Thinking accepts text. Qwen3.5 9B Base handles the widest range of inputs.

Are any of these open source?

Yes, both publish their weights (Apache-2.0 and OpenMDW-1.1), so you can self-host them.

Which is newer?

Trinity Large Thinking is the newest, released Apr 1, 2026. Qwen3.5 9B Base came out Feb 26, 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 Nov 2, 2026.

05 — Keep comparing

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