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Comparison · 3 models · Updated Oct 4, 2026

DeepSeek-R1 vs DeepSeek-V3.1 vs Qwen3 14B

Too close to call on our weighted score (DeepSeek-V3.1 55, Qwen3 14B 54, DeepSeek-R1 51). The right pick depends on what you value most.

  1. DeepSeek

    DeepSeek-R1

    Released Jan 20, 2025

    51/100
    • ECI139.0
    • Price$0.70 / $2.60
    • Context128K
  2. DeepSeek

    DeepSeek-V3.1

    Released Aug 21, 2025

    55/100
    • ECI139.9
    • Price$0.385 / $1.25
    • Context131K
  3. Alibaba (Qwen)

    Qwen3 14B

    Released Apr 29, 2025

    54/100
    • ECI138.2
    • Price$0.35 / $1.40
    • 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, DeepSeek-R1 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 · DeepSeek-R1 139.0 · Qwen3 14B 138.2
  • Lowest priceDeepSeek-V3.1DeepSeek-V3.1 $0.601 · Qwen3 14B $0.613 · DeepSeek-R1 $1.18 per 1M tokens (3:1 blend)
  • Longest contextDeepSeek-V3.1 and Qwen3 14BDeepSeek-V3.1 131,072 · Qwen3 14B 131,072 · DeepSeek-R1 128,000 tokens
  • Widest inputsSame inputsDeepSeek-R1: Text · DeepSeek-V3.1: Text · Qwen3 14B: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightDeepSeek-R1DeepSeek-V3.1Qwen3 14B
CapabilityCapabilities Index (ECI)50%646563
Price25%476060
Inputs & features15%353535
Context window10%242424
Overall100%51/10055/10054/100
02 — Side by side

Every spec in one table

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

DeepSeek-R1 vs DeepSeek-V3.1 vs Qwen3 14B specifications side by side
SpecificationDeepSeek-R1DeepSeekDeepSeek-V3.1DeepSeekQwen3 14BAlibaba (Qwen)
Capability
Capabilities Index (ECI)139.0139.9 (best)138.2
ECI rank#104 of 148#100 of 148 (best)#107 of 148
GPQA DiamondGraduate-level science questions71.7% (best)—63.8%
OTIS Mock AIME 2024–2025Competition mathematics53.3%—66.4% (best)
Price per million tokens
Input$0.70$0.385$0.35 (best)
Output$2.60$1.25 (best)$1.40
Cached input———
Blended (3:1)$1.18$0.601 (best)$0.613
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 11 providersMedian of 8 providersOfficial Alibaba API
Limits
Context window128,000 tokens131,072 tokens (best)131,072 tokens (best)
Max output32,768 tokens (best)8,192 tokens8,192 tokens
Inputs and features
TextYesYesYes
ImagesNoNoNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningYesYesYes
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsOpenOpenMIT LicenseOpen
API model ID——qwen3-14b
API providers12 (best)81
ReleasedJan 20, 2025Aug 21, 2025Apr 29, 2025
Knowledge cutoffJul 2024—Apr 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.

  • DeepSeek-R1$12.20
  • DeepSeek-V3.1$6.35
  • Qwen3 14B$6.30
04 — Questions

Which should you choose?

Which is better: DeepSeek-R1, DeepSeek-V3.1 or Qwen3 14B?

It is close. Our weighted score puts them within 1 points (DeepSeek-V3.1 55/100, Qwen3 14B 54/100, DeepSeek-R1 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, DeepSeek-R1, DeepSeek-V3.1 or Qwen3 14B?

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); DeepSeek-R1 costs $0.70 input / $2.60 output per million tokens (median across 11 API providers). 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 $1.18 for DeepSeek-R1 (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), DeepSeek-R1 139.0 (#104 of 148) and Qwen3 14B 138.2 (#107 of 148). The confidence ranges of the top two overlap (136.1–143.3 vs 136.2–140.4), so treat the gap as small.

Which is better for coding?

There are no published SWE-bench Verified results for DeepSeek-R1, DeepSeek-V3.1 and Qwen3 14B 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?

DeepSeek-V3.1 and Qwen3 14B have the largest context windows (131,072 and 131,072 tokens), against 128,000 for DeepSeek-R1. Maximum output per response: DeepSeek-R1 up to 32,768, DeepSeek-V3.1 up to 8,192, Qwen3 14B up to 8,192 tokens.

Which can read images, PDFs, audio or video?

DeepSeek-R1 accepts text; DeepSeek-V3.1 accepts text; Qwen3 14B 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; DeepSeek-R1 came out Jan 20, 2025. Knowledge cutoff: DeepSeek-R1 Jul 2024, Qwen3 14B 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.