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Comparison · 3 models · Updated Oct 4, 2026

Qwen Plus Character (Japanese) vs Mixtral 8x7B vs Sonar

Too close to call on our weighted score (Mixtral 8x7B 36, Qwen Plus Character (Japanese) 36, Sonar 30). The right pick depends on what you value most.

  1. Alibaba (Qwen)

    Qwen Plus Character (Japanese)

    Released Jan 2024

    36/100
    • ECI—
    • Price$0.50 / $1.40
    • Context8K
    Full specs Remove Qwen Plus Character (Japanese)

  2. Mistral AI

    Mixtral 8x7B

    Released Dec 11, 2023

    36/100
    • ECI118.5
    • Price$0.70 / $0.70
    • Context32K
    Full specs Remove Mixtral 8x7B

  3. Perplexity

    Sonar

    Released Jan 1, 2024

    30/100
    • ECI—
    • Price$1.00 / $1.00
    • Context128K
    Full specs Remove Sonar
01 — Verdict

Too close to call

It is close. Our weighted score puts them within a point (Mixtral 8x7B 36/100, Qwen Plus Character (Japanese) 36/100, Sonar 30/100), so choose by what matters most for your work: Mixtral 8x7B on price and Sonar 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 priceMixtral 8x7BMixtral 8x7B $0.70 · Qwen Plus Character (Japanese) $0.725 · Sonar $1.00 per 1M tokens (3:1 blend)
  • Longest contextSonarSonar 128,000 · Mixtral 8x7B 32,000 · Qwen Plus Character (Japanese) 8,192 tokens
  • Widest inputsSame inputsQwen Plus Character (Japanese): Text · Mixtral 8x7B: Text · Sonar: Text
  • Self-hostingMixtral 8x7BPublishes downloadable weights
How the score is built
MeasureWeightQwen Plus Character (Japanese)Mixtral 8x7BSonar
Price50%575750
Inputs & features30%25250
Context window20%0024
Overall100%36/10036/10030/100

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.

Qwen Plus Character (Japanese) vs Mixtral 8x7B vs Sonar specifications side by side
SpecificationQwen Plus Character (Japanese)Alibaba (Qwen)Mixtral 8x7BMistral AISonarPerplexity
Capability
Capabilities Index (ECI)—118.5—
ECI rank—#142 of 148—
GPQA DiamondGraduate-level science questions—30.6%—
Price per million tokens
Input$0.50 (best)$0.70$1.00
Output$1.40$0.70 (best)$1.00
Cached input———
Blended (3:1)$0.725$0.70 (best)$1.00
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Alibaba APIOfficial Mistral APIOfficial Perplexity API
Limits
Context window8,192 tokens32,000 tokens128,000 tokens (best)
Max output512 tokens32,000 tokens (best)4,096 tokens
Inputs and features
TextYesYesYes
ImagesNoNoNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingYesYesNo
Structured outputNoNoNo
Availability
WeightsProprietaryOpenProprietary
API model IDqwen-plus-character-jaopen-mixtral-8x7bsonar
API providers116 (best)
ReleasedJan 2024Dec 11, 2023Jan 1, 2024
Knowledge cutoffApr 2024Jan 2024Sep 1, 2025
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.

  • Qwen Plus Character (Japanese)$7.80
  • Mixtral 8x7B$8.40
  • Sonar$12.00
04 — Questions

Which should you choose?

Which is better: Qwen Plus Character (Japanese), Mixtral 8x7B or Sonar?

It is close. Our weighted score puts them within a point (Mixtral 8x7B 36/100, Qwen Plus Character (Japanese) 36/100, Sonar 30/100), so choose by what matters most for your work: Mixtral 8x7B on price and Sonar 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, Qwen Plus Character (Japanese), Mixtral 8x7B or Sonar?

Mixtral 8x7B is cheaper at $0.70 input / $0.70 output per million tokens (official Mistral API price). Qwen Plus Character (Japanese) costs $0.50 input / $1.40 output per million tokens (official Alibaba API price); Sonar costs $1.00 input / $1.00 output per million tokens (official Perplexity API price). At a typical mix of three input tokens to one output token, that is $0.70 per million tokens for Mixtral 8x7B versus $0.725 for Qwen Plus Character (Japanese) (1× as much) and $1.00 for Sonar (1.4× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. Qwen Plus Character (Japanese) has not been scored yet, Mixtral 8x7B has an ECI of 118.5 and Sonar has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen Plus Character (Japanese), Mixtral 8x7B and Sonar yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Sonar does not support tool calling, which most coding agents need.

Which has the bigger context window?

Sonar has the largest context window at 128,000 tokens, against 32,000 for Mixtral 8x7B and 8,192 for Qwen Plus Character (Japanese). Maximum output per response: Qwen Plus Character (Japanese) up to 512, Mixtral 8x7B up to 32,000, Sonar up to 4,096 tokens.

Which can read images, PDFs, audio or video?

Qwen Plus Character (Japanese) accepts text; Mixtral 8x7B accepts text; Sonar accepts text. They handle the same number of input types.

Are any of these open source?

Mixtral 8x7B publishes its weights and can be self-hosted; Qwen Plus Character (Japanese) and Sonar is proprietary.

Which is newer?

Qwen Plus Character (Japanese) is the newest, released Jan 2024. Sonar came out Jan 1, 2024; Mixtral 8x7B came out Dec 11, 2023. Knowledge cutoff: Qwen Plus Character (Japanese) Apr 2024, Mixtral 8x7B Jan 2024, Sonar Sep 1, 2025.

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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