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Comparison · 3 models · Updated Oct 4, 2026

Gemini 2.5 Computer Use Preview vs Qwen3-VL Plus vs GPT-5-Codex

Qwen3-VL Plus comes out ahead, 56 to 42 and 35 on our weighted score, and it is the cheaper option too.

  1. Google

    Gemini 2.5 Computer Use Preview

    Released Oct 7, 2025

    35/100
    • ECI—
    • Price$1.25 / $10.00
    • Context128K
  2. Our pick

    Alibaba (Qwen)

    Qwen3-VL Plus

    Released Sep 23, 2025

    56/100
    • ECI—
    • Price$0.20 / $1.60
    • Context262K
  3. OpenAI

    GPT-5-Codex

    Released Sep 15, 2025

    42/100
    • ECI—
    • Price$1.25 / $10.00
    • Context400K
01 — Verdict

Qwen3-VL Plus is our pick

Qwen3-VL Plus is the better all-round choice, scoring 56/100 against GPT-5-Codex (42) and Gemini 2.5 Computer Use Preview (35). It leads on price. GPT-5-Codex wins on inputs & features and context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

  • CapabilityNot enough dataNo independent benchmark covers every model here yet
  • Lowest priceQwen3-VL PlusQwen3-VL Plus $0.55 · Gemini 2.5 Computer Use Preview $3.44 · GPT-5-Codex $3.44 per 1M tokens (3:1 blend)
  • Longest contextGPT-5-CodexGPT-5-Codex 400,000 · Qwen3-VL Plus 262,144 · Gemini 2.5 Computer Use Preview 128,000 tokens
  • Widest inputsSame inputsGemini 2.5 Computer Use Preview: Text, Images · Qwen3-VL Plus: Text, Images · GPT-5-Codex: Text, Images
  • Self-hostingNo open weightsAll three are available only through APIs
How the score is built
MeasureWeightGemini 2.5 Computer Use PreviewQwen3-VL PlusGPT-5-Codex
Price50%246224
Inputs & features30%606070
Context window20%243744
Overall100%35/10056/10042/100

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

Gemini 2.5 Computer Use Preview vs Qwen3-VL Plus vs GPT-5-Codex specifications side by side
SpecificationGemini 2.5 Computer Use PreviewGoogleQwen3-VL PlusAlibaba (Qwen)GPT-5-CodexOpenAI
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
Input$1.25$0.20 (best)$1.25
Output$10.00$1.60 (best)$10.00
Cached input———
Blended (3:1)$3.44$0.55 (best)$3.44
Long-context rateOver 200K: $2.50 / $15.00Same rateSame rate
Price sourceOfficial Google APIOfficial Alibaba APIMedian of 3 providers
Limits
Context window128,000 tokens262,144 tokens400,000 tokens (best)
Max output64,000 tokens32,768 tokens128,000 tokens (best)
Inputs and features
TextYesYesYes
ImagesYesYesYes
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningYesYesYes
Tool callingYesYesYes
Structured outputNoNoYes
Availability
WeightsProprietaryProprietaryProprietary
API model IDgemini-2.5-computer-use-preview-10-2025qwen3-vl-plus—
API providers26 (best)3
ReleasedOct 7, 2025Sep 23, 2025Sep 15, 2025
Knowledge cutoffJan 2025Apr 2025Sep 30, 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.

  • Gemini 2.5 Computer Use Preview$32.50
  • Qwen3-VL Plus$5.20
  • GPT-5-Codex$32.50
04 — Questions

Which should you choose?

Which is better: Gemini 2.5 Computer Use Preview, Qwen3-VL Plus or GPT-5-Codex?

Qwen3-VL Plus is the better all-round choice, scoring 56/100 against GPT-5-Codex (42) and Gemini 2.5 Computer Use Preview (35). It leads on price. GPT-5-Codex wins on inputs & features and context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

Which is cheaper, Gemini 2.5 Computer Use Preview, Qwen3-VL Plus or GPT-5-Codex?

Qwen3-VL Plus is cheaper at $0.20 input / $1.60 output per million tokens (official Alibaba API price). Gemini 2.5 Computer Use Preview costs $1.25 input / $10.00 output per million tokens (official Google API price); GPT-5-Codex costs $1.25 input / $10.00 output per million tokens (median across 3 API providers). At a typical mix of three input tokens to one output token, that is $0.55 per million tokens for Qwen3-VL Plus versus $3.44 for Gemini 2.5 Computer Use Preview (6.2× as much) and $3.44 for GPT-5-Codex (6.2× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. Gemini 2.5 Computer Use Preview has not been scored yet, Qwen3-VL Plus has not been scored yet and GPT-5-Codex has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Gemini 2.5 Computer Use Preview, Qwen3-VL Plus and GPT-5-Codex yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.

Which has the bigger context window?

GPT-5-Codex has the largest context window at 400,000 tokens, against 262,144 for Qwen3-VL Plus and 128,000 for Gemini 2.5 Computer Use Preview. Maximum output per response: Gemini 2.5 Computer Use Preview up to 64,000, Qwen3-VL Plus up to 32,768, GPT-5-Codex up to 128,000 tokens.

Which can read images, PDFs, audio or video?

Gemini 2.5 Computer Use Preview accepts text and images; Qwen3-VL Plus accepts text and images; GPT-5-Codex accepts text and images. They handle the same number of input types.

Are any of these open source?

No. Gemini 2.5 Computer Use Preview, Qwen3-VL Plus and GPT-5-Codex are proprietary and only available through APIs and apps.

Which is newer?

Gemini 2.5 Computer Use Preview is the newest, released Oct 7, 2025. Qwen3-VL Plus came out Sep 23, 2025; GPT-5-Codex came out Sep 15, 2025. Knowledge cutoff: Gemini 2.5 Computer Use Preview Jan 2025, Qwen3-VL Plus Apr 2025, GPT-5-Codex Sep 30, 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 Oct 4, 2026.