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Comparison · 3 models · Updated Nov 2, 2026

Qwen3 235B-A22B Instruct 2507 vs DeepSeek R1 0528 vs GPT OSS 120B

Too close to call on our weighted score (GPT OSS 120B 58, Qwen3 235B-A22B Instruct 2507 57, DeepSeek R1 0528 53). The right pick depends on what you value most.

  1. Alibaba (Qwen)

    Qwen3 235B-A22B Instruct 2507

    Released Jul 21, 2025

    57/100
    • ECI138.8
    • Price$0.199 / $0.60
    • Context262K
  2. DeepSeek

    DeepSeek R1 0528

    Released May 28, 2025

    53/100
    • ECI141.2
    • Price$0.512 / $2.19
    • Context164K
  3. OpenAI

    GPT OSS 120B

    Released Aug 5, 2025

    58/100
    • ECI139.8
    • Price$0.15 / $0.60
    • Context131K
01 — Verdict

Too close to call

It is close. Our weighted score puts them within 2 points (GPT OSS 120B 58/100, Qwen3 235B-A22B Instruct 2507 57/100, DeepSeek R1 0528 53/100), so choose by what matters most for your work: DeepSeek R1 0528 for raw capability, GPT OSS 120B on price and Qwen3 235B-A22B Instruct 2507 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityDeepSeek R1 0528Capabilities Index (ECI): DeepSeek R1 0528 141.2 · GPT OSS 120B 139.8 · Qwen3 235B-A22B Instruct 2507 138.8
  • Lowest priceGPT OSS 120BGPT OSS 120B $0.263 · Qwen3 235B-A22B Instruct 2507 $0.299 · DeepSeek R1 0528 $0.932 per 1M tokens (3:1 blend)
  • Longest contextQwen3 235B-A22B Instruct 2507Qwen3 235B-A22B Instruct 2507 262,144 · DeepSeek R1 0528 163,840 · GPT OSS 120B 131,072 tokens
  • Widest inputsSame inputsQwen3 235B-A22B Instruct 2507: Text · DeepSeek R1 0528: Text · GPT OSS 120B: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightQwen3 235B-A22B Instruct 2507DeepSeek R1 0528GPT OSS 120B
CapabilityCapabilities Index (ECI)50%636664
Price25%724974
Inputs & features15%253535
Context window10%372825
Overall100%57/10053/10058/100
02 — Side by side

Every spec in one table

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

Qwen3 235B-A22B Instruct 2507 vs DeepSeek R1 0528 vs GPT OSS 120B specifications side by side
SpecificationQwen3 235B-A22B Instruct 2507Alibaba (Qwen)DeepSeek R1 0528DeepSeekGPT OSS 120BOpenAI
Capability
Capabilities Index (ECI)138.8141.2 (best)139.8
ECI rank#118 of 165#108 of 165 (best)#114 of 165
GPQA DiamondGraduate-level science questions—76.3% (best)75.8%
OTIS Mock AIME 2024–2025Competition mathematics—66.4%88.9% (best)
Price per million tokens
Input$0.199$0.512$0.15 (best)
Output$0.60 (best)$2.19$0.60 (best)
Cached input———
Blended (3:1)$0.299$0.932$0.263 (best)
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 23 providersMedian of 16 providersMedian of 65 providers
Limits
Context window262,144 tokens (best)163,840 tokens131,072 tokens
Max output16,384 tokens32,768 tokens (best)32,768 tokens (best)
Inputs and features
TextYesYesYes
ImagesNoNoNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoYesYes
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsOpenApache 2.0OpenMITOpen
API model ID———
API providers251667 (best)
ReleasedJul 21, 2025May 28, 2025Aug 5, 2025
Knowledge cutoff——Jun 2024
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 235B-A22B Instruct 2507$3.19
  • DeepSeek R1 0528$9.50
  • GPT OSS 120B$2.70
04 — Questions

Which should you choose?

Which is better: Qwen3 235B-A22B Instruct 2507, DeepSeek R1 0528 or GPT OSS 120B?

It is close. Our weighted score puts them within 2 points (GPT OSS 120B 58/100, Qwen3 235B-A22B Instruct 2507 57/100, DeepSeek R1 0528 53/100), so choose by what matters most for your work: DeepSeek R1 0528 for raw capability, GPT OSS 120B on price and Qwen3 235B-A22B Instruct 2507 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Qwen3 235B-A22B Instruct 2507, DeepSeek R1 0528 or GPT OSS 120B?

GPT OSS 120B is cheaper at $0.15 input / $0.60 output per million tokens (median across 65 API providers). Qwen3 235B-A22B Instruct 2507 costs $0.199 input / $0.60 output per million tokens (median across 23 API providers); DeepSeek R1 0528 costs $0.512 input / $2.19 output per million tokens (median across 16 API providers). At a typical mix of three input tokens to one output token, that is $0.263 per million tokens for GPT OSS 120B versus $0.299 for Qwen3 235B-A22B Instruct 2507 (1.1× as much) and $0.932 for DeepSeek R1 0528 (3.6× as much).

Which scores higher on benchmarks?

DeepSeek R1 0528 scores higher on the Capabilities Index (ECI): DeepSeek R1 0528 141.2 (#108 of 165), GPT OSS 120B 139.8 (#114 of 165) and Qwen3 235B-A22B Instruct 2507 138.8 (#118 of 165). The confidence ranges of the top two overlap (139.0–142.9 vs 135.6–142.2), so treat the gap as small.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen3 235B-A22B Instruct 2507, DeepSeek R1 0528 and GPT OSS 120B yet, so there is no like-for-like coding score. On overall capability, DeepSeek R1 0528 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 235B-A22B Instruct 2507 has the largest context window at 262,144 tokens, against 163,840 for DeepSeek R1 0528 and 131,072 for GPT OSS 120B. Maximum output per response: Qwen3 235B-A22B Instruct 2507 up to 16,384, DeepSeek R1 0528 up to 32,768, GPT OSS 120B up to 32,768 tokens.

Which can read images, PDFs, audio or video?

Qwen3 235B-A22B Instruct 2507 accepts text; DeepSeek R1 0528 accepts text; GPT OSS 120B accepts text. They handle the same number of input types.

Are any of these open source?

Yes, all three publish their weights (Apache 2.0 and MIT), so you can self-host them.

Which is newer?

GPT OSS 120B is the newest, released Aug 5, 2025. Qwen3 235B-A22B Instruct 2507 came out Jul 21, 2025; DeepSeek R1 0528 came out May 28, 2025. Knowledge cutoff: GPT OSS 120B Jun 2024.

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 Nov 2, 2026.