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Comparison · 3 models · Updated Oct 4, 2026

Qwen3 14B vs Qwen3 235B-A22B vs DeepSeek-V3.1

Too close to call on our weighted score (DeepSeek-V3.1 55, Qwen3 14B 54, Qwen3 235B-A22B 51). The right pick depends on what you value most.

  1. Alibaba (Qwen)

    Qwen3 14B

    Released Apr 29, 2025

    54/100
    • ECI138.2
    • Price$0.35 / $1.40
    • Context131K
  2. Alibaba (Qwen)

    Qwen3 235B-A22B

    Released Apr 28, 2025

    51/100
    • ECI139.4
    • Price$0.70 / $2.80
    • Context131K
  3. DeepSeek

    DeepSeek-V3.1

    Released Aug 21, 2025

    55/100
    • ECI139.9
    • Price$0.385 / $1.25
    • Context131K
01 — Verdict

Too close to call

It is close. Our weighted score puts them within 1 points (DeepSeek-V3.1 55/100, Qwen3 14B 54/100, Qwen3 235B-A22B 51/100), so choose by what matters most for your work: DeepSeek-V3.1 for raw capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityDeepSeek-V3.1Capabilities Index (ECI): DeepSeek-V3.1 139.9 · Qwen3 235B-A22B 139.4 · Qwen3 14B 138.2
  • Lowest priceDeepSeek-V3.1DeepSeek-V3.1 $0.601 · Qwen3 14B $0.613 · Qwen3 235B-A22B $1.23 per 1M tokens (3:1 blend)
  • Longest contextAbout the sameQwen3 14B 131,072 · Qwen3 235B-A22B 131,072 · DeepSeek-V3.1 131,072 tokens
  • Widest inputsSame inputsQwen3 14B: Text · Qwen3 235B-A22B: Text · DeepSeek-V3.1: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightQwen3 14BQwen3 235B-A22BDeepSeek-V3.1
CapabilityCapabilities Index (ECI)50%636565
Price25%604660
Inputs & features15%353535
Context window10%242424
Overall100%54/10051/10055/100
02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

Qwen3 14B vs Qwen3 235B-A22B vs DeepSeek-V3.1 specifications side by side
SpecificationQwen3 14BAlibaba (Qwen)Qwen3 235B-A22BAlibaba (Qwen)DeepSeek-V3.1DeepSeek
Capability
Capabilities Index (ECI)138.2139.4139.9 (best)
ECI rank#107 of 148#103 of 148#100 of 148 (best)
GPQA DiamondGraduate-level science questions63.8%70.7% (best)—
OTIS Mock AIME 2024–2025Competition mathematics66.4%——
Price per million tokens
Input$0.35 (best)$0.70$0.385
Output$1.40$2.80$1.25 (best)
Cached input———
Blended (3:1)$0.613$1.23$0.601 (best)
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Alibaba APIOfficial Alibaba APIMedian of 8 providers
Limits
Context window131,072 tokens131,072 tokens131,072 tokens
Max output8,192 tokens16,384 tokens (best)8,192 tokens
Inputs and features
TextYesYesYes
ImagesNoNoNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningYesYesYes
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsOpenOpenOpenMIT License
API model IDqwen3-14bqwen3-235b-a22b—
API providers178 (best)
ReleasedApr 29, 2025Apr 28, 2025Aug 21, 2025
Knowledge cutoffApr 2025Apr 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.

  • Qwen3 14B$6.30
  • Qwen3 235B-A22B$12.60
  • DeepSeek-V3.1$6.35
04 — Questions

Which should you choose?

Which is better: Qwen3 14B, Qwen3 235B-A22B or DeepSeek-V3.1?

It is close. Our weighted score puts them within 1 points (DeepSeek-V3.1 55/100, Qwen3 14B 54/100, Qwen3 235B-A22B 51/100), so choose by what matters most for your work: DeepSeek-V3.1 for raw capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Qwen3 14B, Qwen3 235B-A22B or DeepSeek-V3.1?

DeepSeek-V3.1 is cheaper at $0.385 input / $1.25 output per million tokens (median across 8 API providers). Qwen3 14B costs $0.35 input / $1.40 output per million tokens (official Alibaba API price); Qwen3 235B-A22B costs $0.70 input / $2.80 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.601 per million tokens for DeepSeek-V3.1 versus $0.613 for Qwen3 14B (1× as much) and $1.23 for Qwen3 235B-A22B (2× as much).

Which scores higher on benchmarks?

DeepSeek-V3.1 scores higher on the Capabilities Index (ECI): DeepSeek-V3.1 139.9 (#100 of 148), Qwen3 235B-A22B 139.4 (#103 of 148) and Qwen3 14B 138.2 (#107 of 148). The confidence ranges of the top two overlap (136.1–143.3 vs 135.2–140.8), so treat the gap as small.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen3 14B, Qwen3 235B-A22B and DeepSeek-V3.1 yet, so there is no like-for-like coding score. On overall capability, DeepSeek-V3.1 leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.

Which has the bigger context window?

Qwen3 14B, Qwen3 235B-A22B and DeepSeek-V3.1 share the same 131,072-token context window. Maximum output per response: Qwen3 14B up to 8,192, Qwen3 235B-A22B up to 16,384, DeepSeek-V3.1 up to 8,192 tokens.

Which can read images, PDFs, audio or video?

Qwen3 14B accepts text; Qwen3 235B-A22B accepts text; DeepSeek-V3.1 accepts text. They handle the same number of input types.

Are any of these open source?

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

Which is newer?

DeepSeek-V3.1 is the newest, released Aug 21, 2025. Qwen3 14B came out Apr 29, 2025; Qwen3 235B-A22B came out Apr 28, 2025. Knowledge cutoff: Qwen3 14B Apr 2025, Qwen3 235B-A22B Apr 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.