ZMIME
Comparison · 3 models · Updated Oct 4, 2026

DeepSeek-R1-Distill-Qwen-32B vs GPT-4.1 vs Qwen3 32B

GPT-4.1 comes out ahead, 63 to 53 and 47 on our weighted score, though Qwen3 32B is 2.9× cheaper per token.

  1. DeepSeek

    DeepSeek-R1-Distill-Qwen-32B

    Released Jan 20, 2025

    47/100
    • ECI137.4
    • Price—
    • Context131K
  2. Our pick

    OpenAI

    GPT-4.1

    Released Apr 14, 2025

    63/100
    • ECI136.8
    • Price$2.00 / $8.00
    • Context1.05M
  3. Alibaba (Qwen)

    Qwen3 32B

    Released Apr 29, 2025

    53/100
    • ECI138.5
    • Price$0.70 / $2.80
    • Context131K
01 — Verdict

GPT-4.1 is our pick

GPT-4.1 is the better all-round choice, scoring 63/100 against Qwen3 32B (53) and DeepSeek-R1-Distill-Qwen-32B (47). It leads on inputs & features and context window. The score weighs capability 67%, inputs & features 20%, context window 13%.

  • CapabilityQwen3 32BCapabilities Index (ECI): Qwen3 32B 138.5 · DeepSeek-R1-Distill-Qwen-32B 137.4 · GPT-4.1 136.8
  • Lowest priceQwen3 32BQwen3 32B $1.23 · GPT-4.1 $3.50 per 1M tokens (3:1 blend) · DeepSeek-R1-Distill-Qwen-32B unpriced
  • Longest contextGPT-4.1GPT-4.1 1,047,576 · DeepSeek-R1-Distill-Qwen-32B 131,072 · Qwen3 32B 131,072 tokens
  • Widest inputsGPT-4.1DeepSeek-R1-Distill-Qwen-32B: Text · GPT-4.1: Text, Images, PDFs · Qwen3 32B: Text
  • Self-hostingDeepSeek-R1-Distill-Qwen-32B and Qwen3 32BPublishes downloadable weights
How the score is built
MeasureWeightDeepSeek-R1-Distill-Qwen-32BGPT-4.1Qwen3 32B
CapabilityCapabilities Index (ECI)67%626164
Inputs & features20%107035
Context window13%246124
Overall100%47/10063/10053/100

Left out because at least one model lacks the data: price. 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.

DeepSeek-R1-Distill-Qwen-32B vs GPT-4.1 vs Qwen3 32B specifications side by side
SpecificationDeepSeek-R1-Distill-Qwen-32BDeepSeekGPT-4.1OpenAIQwen3 32BAlibaba (Qwen)
Capability
Capabilities Index (ECI)137.4136.8138.5 (best)
ECI rank#110 of 148#111 of 148#106 of 148 (best)
GPQA DiamondGraduate-level science questions64.1%66.9% (best)65.7%
FrontierMath Tiers 1–3Research-level mathematics—6.0%—
OTIS Mock AIME 2024–2025Competition mathematics55.6%38.3%66.9% (best)
SWE-bench VerifiedFixing real GitHub issues—48.5%—
SimpleQA VerifiedShort factual questions—31.1%—
Price per million tokens
Input—$2.00$0.70 (best)
Output—$8.00$2.80 (best)
Cached input—$0.50—
Blended (3:1)—$3.50$1.23 (best)
Long-context rate—Same rateSame rate
Price source—Official OpenAI APIOfficial Alibaba API
Limits
Context window131,072 tokens1,047,576 tokens (best)131,072 tokens
Max output32,768 tokens (best)32,768 tokens (best)16,384 tokens
Inputs and features
TextYesYesYes
ImagesNoYesNo
PDFsNoYesNo
AudioNoNoNo
VideoNoNoNo
ReasoningYesNoYes
Tool callingNoYesYes
Structured outputNoYesNo
Availability
WeightsOpenProprietaryOpen
API model ID—gpt-4.1qwen3-32b
API providers—25 (best)14
ReleasedJan 20, 2025Apr 14, 2025Apr 29, 2025
Knowledge cutoff—Apr 2024Apr 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-Distill-Qwen-32B—
  • GPT-4.1$36.00
  • Qwen3 32B$12.60
04 — Questions

Which should you choose?

Which is better: DeepSeek-R1-Distill-Qwen-32B, GPT-4.1 or Qwen3 32B?

GPT-4.1 is the better all-round choice, scoring 63/100 against Qwen3 32B (53) and DeepSeek-R1-Distill-Qwen-32B (47). It leads on inputs & features and context window. The score weighs capability 67%, inputs & features 20%, context window 13%.

Which is cheaper, DeepSeek-R1-Distill-Qwen-32B, GPT-4.1 or Qwen3 32B?

Qwen3 32B is cheaper at $0.70 input / $2.80 output per million tokens (official Alibaba API price). GPT-4.1 costs $2.00 input / $8.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $1.23 per million tokens for Qwen3 32B versus $3.50 for GPT-4.1 (2.9× as much). DeepSeek-R1-Distill-Qwen-32B has no published per-token price.

Which scores higher on benchmarks?

Qwen3 32B scores higher on the Capabilities Index (ECI): Qwen3 32B 138.5 (#106 of 148), DeepSeek-R1-Distill-Qwen-32B 137.4 (#110 of 148) and GPT-4.1 136.8 (#111 of 148). The confidence ranges of the top two overlap (135.1–140.4 vs 130.7–138.7), so treat the gap as small. On individual benchmarks: GPQA Diamond — GPT-4.1 66.9%, Qwen3 32B 65.7%, DeepSeek-R1-Distill-Qwen-32B 64.1%; OTIS Mock AIME 2024–2025 — Qwen3 32B 66.9%, DeepSeek-R1-Distill-Qwen-32B 55.6%, GPT-4.1 38.3%.

Which is better for coding?

There are no published SWE-bench Verified results for DeepSeek-R1-Distill-Qwen-32B and Qwen3 32B yet, so there is no like-for-like coding score. On overall capability, Qwen3 32B leads, which tends to carry over to coding, but test on your own codebase. Note that DeepSeek-R1-Distill-Qwen-32B does not support tool calling, which most coding agents need.

Which has the bigger context window?

GPT-4.1 has the largest context window at 1,047,576 tokens, against 131,072 for DeepSeek-R1-Distill-Qwen-32B and 131,072 for Qwen3 32B. Maximum output per response: DeepSeek-R1-Distill-Qwen-32B up to 32,768, GPT-4.1 up to 32,768, Qwen3 32B up to 16,384 tokens.

Which can read images, PDFs, audio or video?

DeepSeek-R1-Distill-Qwen-32B accepts text; GPT-4.1 accepts text, images and PDFs; Qwen3 32B accepts text. GPT-4.1 handles the widest range of inputs.

Are any of these open source?

DeepSeek-R1-Distill-Qwen-32B and Qwen3 32B publishes its weights and can be self-hosted; GPT-4.1 is proprietary.

Which is newer?

Qwen3 32B is the newest, released Apr 29, 2025. GPT-4.1 came out Apr 14, 2025; DeepSeek-R1-Distill-Qwen-32B came out Jan 20, 2025. Knowledge cutoff: GPT-4.1 Apr 2024, Qwen3 32B 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.