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Comparison · 3 models · Updated Oct 4, 2026

DeepSeek-R1 vs GPT-4.1 vs Qwen3 235B-A22B

Too close to call on our weighted score (GPT-4.1 53, Qwen3 235B-A22B 51, 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. OpenAI

    GPT-4.1

    Released Apr 14, 2025

    53/100
    • ECI136.8
    • Price$2.00 / $8.00
    • Context1.05M
  3. Alibaba (Qwen)

    Qwen3 235B-A22B

    Released Apr 28, 2025

    51/100
    • ECI139.4
    • Price$0.70 / $2.80
    • Context131K
01 — Verdict

Too close to call

It is close. Our weighted score puts them within 2 points (GPT-4.1 53/100, Qwen3 235B-A22B 51/100, DeepSeek-R1 51/100), so choose by what matters most for your work: Qwen3 235B-A22B for raw capability, DeepSeek-R1 on price and GPT-4.1 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityQwen3 235B-A22BCapabilities Index (ECI): Qwen3 235B-A22B 139.4 · DeepSeek-R1 139.0 · GPT-4.1 136.8
  • Lowest priceDeepSeek-R1DeepSeek-R1 $1.18 · Qwen3 235B-A22B $1.23 · GPT-4.1 $3.50 per 1M tokens (3:1 blend)
  • Longest contextGPT-4.1GPT-4.1 1,047,576 · Qwen3 235B-A22B 131,072 · DeepSeek-R1 128,000 tokens
  • Widest inputsGPT-4.1DeepSeek-R1: Text · GPT-4.1: Text, Images, PDFs · Qwen3 235B-A22B: Text
  • Self-hostingDeepSeek-R1 and Qwen3 235B-A22BPublishes downloadable weights
How the score is built
MeasureWeightDeepSeek-R1GPT-4.1Qwen3 235B-A22B
CapabilityCapabilities Index (ECI)50%646165
Price25%472446
Inputs & features15%357035
Context window10%246124
Overall100%51/10053/10051/100
02 — Side by side

Every spec in one table

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

DeepSeek-R1 vs GPT-4.1 vs Qwen3 235B-A22B specifications side by side
SpecificationDeepSeek-R1DeepSeekGPT-4.1OpenAIQwen3 235B-A22BAlibaba (Qwen)
Capability
Capabilities Index (ECI)139.0136.8139.4 (best)
ECI rank#104 of 148#111 of 148#103 of 148 (best)
GPQA DiamondGraduate-level science questions71.7% (best)66.9%70.7%
FrontierMath Tiers 1–3Research-level mathematics—6.0%—
OTIS Mock AIME 2024–2025Competition mathematics53.3% (best)38.3%—
SWE-bench VerifiedFixing real GitHub issues—48.5%—
SimpleQA VerifiedShort factual questions—31.1%—
Price per million tokens
Input$0.70 (best)$2.00$0.70 (best)
Output$2.60 (best)$8.00$2.80
Cached input—$0.50—
Blended (3:1)$1.18 (best)$3.50$1.23
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 11 providersOfficial OpenAI APIOfficial Alibaba API
Limits
Context window128,000 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 callingYesYesYes
Structured outputNoYesNo
Availability
WeightsOpenProprietaryOpen
API model ID—gpt-4.1qwen3-235b-a22b
API providers1225 (best)7
ReleasedJan 20, 2025Apr 14, 2025Apr 28, 2025
Knowledge cutoffJul 2024Apr 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$12.20
  • GPT-4.1$36.00
  • Qwen3 235B-A22B$12.60
04 — Questions

Which should you choose?

Which is better: DeepSeek-R1, GPT-4.1 or Qwen3 235B-A22B?

It is close. Our weighted score puts them within 2 points (GPT-4.1 53/100, Qwen3 235B-A22B 51/100, DeepSeek-R1 51/100), so choose by what matters most for your work: Qwen3 235B-A22B for raw capability, DeepSeek-R1 on price and GPT-4.1 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, DeepSeek-R1, GPT-4.1 or Qwen3 235B-A22B?

DeepSeek-R1 is cheaper at $0.70 input / $2.60 output per million tokens (median across 11 API providers). Qwen3 235B-A22B costs $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 $1.18 per million tokens for DeepSeek-R1 versus $1.23 for Qwen3 235B-A22B (1× as much) and $3.50 for GPT-4.1 (3× as much).

Which scores higher on benchmarks?

Qwen3 235B-A22B scores higher on the Capabilities Index (ECI): Qwen3 235B-A22B 139.4 (#103 of 148), DeepSeek-R1 139.0 (#104 of 148) and GPT-4.1 136.8 (#111 of 148). The confidence ranges of the top two overlap (135.2–140.8 vs 136.2–140.4), so treat the gap as small. On individual benchmarks: GPQA Diamond — DeepSeek-R1 71.7%, Qwen3 235B-A22B 70.7%, GPT-4.1 66.9%.

Which is better for coding?

There are no published SWE-bench Verified results for DeepSeek-R1 and Qwen3 235B-A22B yet, so there is no like-for-like coding score. On overall capability, Qwen3 235B-A22B 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?

GPT-4.1 has the largest context window at 1,047,576 tokens, against 131,072 for Qwen3 235B-A22B and 128,000 for DeepSeek-R1. Maximum output per response: DeepSeek-R1 up to 32,768, GPT-4.1 up to 32,768, Qwen3 235B-A22B up to 16,384 tokens.

Which can read images, PDFs, audio or video?

DeepSeek-R1 accepts text; GPT-4.1 accepts text, images and PDFs; Qwen3 235B-A22B accepts text. GPT-4.1 handles the widest range of inputs.

Are any of these open source?

DeepSeek-R1 and Qwen3 235B-A22B publishes its weights and can be self-hosted; GPT-4.1 is proprietary.

Which is newer?

Qwen3 235B-A22B is the newest, released Apr 28, 2025. GPT-4.1 came out Apr 14, 2025; DeepSeek-R1 came out Jan 20, 2025. Knowledge cutoff: DeepSeek-R1 Jul 2024, GPT-4.1 Apr 2024, 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.