ZMIME
Comparison · 3 models · Updated Oct 4, 2026

Gemini 2.5 Pro vs Qwen3.5 397B-A17B vs o3

Too close to call on our weighted score (Qwen3.5 397B-A17B 65, Gemini 2.5 Pro 63, o3 58). The right pick depends on what you value most.

  1. Google

    Gemini 2.5 Pro

    Released Jun 17, 2025

    63/100
    • ECI145.3
    • Price$1.25 / $10.00
    • Context1.05M
  2. Alibaba (Qwen)

    Qwen3.5 397B-A17B

    Released Feb 15, 2026

    65/100
    • ECI146.7
    • Price$0.60 / $3.60
    • Context262K
  3. OpenAI

    o3

    Released Apr 16, 2025

    58/100
    • ECI146.9
    • Price$2.00 / $8.00
    • Context200K
01 — Verdict

Too close to call

It is close. Our weighted score puts them within 2 points (Qwen3.5 397B-A17B 65/100, Gemini 2.5 Pro 63/100, o3 58/100), so choose by what matters most for your work: o3 for raw capability, Qwen3.5 397B-A17B on price and Gemini 2.5 Pro for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • Capabilityo3Capabilities Index (ECI): o3 146.9 · Qwen3.5 397B-A17B 146.7 · Gemini 2.5 Pro 145.3
  • Lowest priceQwen3.5 397B-A17BQwen3.5 397B-A17B $1.35 · Gemini 2.5 Pro $3.44 · o3 $3.50 per 1M tokens (3:1 blend)
  • Longest contextGemini 2.5 ProGemini 2.5 Pro 1,048,576 · Qwen3.5 397B-A17B 262,144 · o3 200,000 tokens
  • Widest inputsGemini 2.5 ProGemini 2.5 Pro: Text, Images, PDFs, Audio, Video · Qwen3.5 397B-A17B: Text, Images, Audio, Video · o3: Text, Images, PDFs
  • Self-hostingQwen3.5 397B-A17BPublishes downloadable weights
How the score is built
MeasureWeightGemini 2.5 ProQwen3.5 397B-A17Bo3
CapabilityCapabilities Index (ECI)50%727474
Price25%244424
Inputs & features15%1009080
Context window10%613732
Overall100%63/10065/10058/100
02 — Side by side

Every spec in one table

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

Gemini 2.5 Pro vs Qwen3.5 397B-A17B vs o3 specifications side by side
SpecificationGemini 2.5 ProGoogleQwen3.5 397B-A17BAlibaba (Qwen)o3OpenAI
Capability
Capabilities Index (ECI)145.3146.7146.9 (best)
ECI rank#78 of 148#67 of 148#63 of 148 (best)
GPQA DiamondGraduate-level science questions85.3%86.4% (best)81.8%
FrontierMath Tiers 1–3Research-level mathematics24.6%31.2%33.3% (best)
OTIS Mock AIME 2024–2025Competition mathematics84.7%88.9% (best)84.4%
SWE-bench VerifiedFixing real GitHub issues57.6%—62.3% (best)
SimpleQA VerifiedShort factual questions——49.4%
Price per million tokens
Input$1.25$0.60 (best)$2.00
Output$10.00$3.60 (best)$8.00
Cached input$0.125 (best)—$0.50
Blended (3:1)$3.44$1.35 (best)$3.50
Long-context rateOver 200K: $2.50 / $15.00Same rateSame rate
Price sourceOfficial Google APIOfficial Alibaba APIOfficial OpenAI API
Limits
Context window1,048,576 tokens (best)262,144 tokens200,000 tokens
Max output65,536 tokens65,536 tokens100,000 tokens (best)
Inputs and features
TextYesYesYes
ImagesYesYesYes
PDFsYesNoYes
AudioYesYesNo
VideoYesYesNo
ReasoningYesYesYeslow · medium · high
Tool callingYesYesYes
Structured outputYesYesYes
Availability
WeightsProprietaryOpenProprietary
API model IDgemini-2.5-proqwen3.5-397b-a17bo3
API providers2223 (best)18
ReleasedJun 17, 2025Feb 15, 2026Apr 16, 2025
Knowledge cutoffJan 2025—May 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 Pro$32.50
  • Qwen3.5 397B-A17B$13.20
  • o3$36.00
04 — Questions

Which should you choose?

Which is better: Gemini 2.5 Pro, Qwen3.5 397B-A17B or o3?

It is close. Our weighted score puts them within 2 points (Qwen3.5 397B-A17B 65/100, Gemini 2.5 Pro 63/100, o3 58/100), so choose by what matters most for your work: o3 for raw capability, Qwen3.5 397B-A17B on price and Gemini 2.5 Pro for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Gemini 2.5 Pro, Qwen3.5 397B-A17B or o3?

Qwen3.5 397B-A17B is cheaper at $0.60 input / $3.60 output per million tokens (official Alibaba API price). Gemini 2.5 Pro costs $1.25 input / $10.00 output per million tokens (official Google API price); o3 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 $1.35 per million tokens for Qwen3.5 397B-A17B versus $3.44 for Gemini 2.5 Pro (2.5× as much) and $3.50 for o3 (2.6× as much).

Which scores higher on benchmarks?

o3 scores higher on the Capabilities Index (ECI): o3 146.9 (#63 of 148), Qwen3.5 397B-A17B 146.7 (#67 of 148) and Gemini 2.5 Pro 145.3 (#78 of 148). The confidence ranges of the top two overlap (144.9–148.6 vs 144.8–148.2), so treat the gap as small. On individual benchmarks: GPQA Diamond — Qwen3.5 397B-A17B 86.4%, Gemini 2.5 Pro 85.3%, o3 81.8%; FrontierMath Tiers 1–3 — o3 33.3%, Qwen3.5 397B-A17B 31.2%, Gemini 2.5 Pro 24.6%; OTIS Mock AIME 2024–2025 — Qwen3.5 397B-A17B 88.9%, Gemini 2.5 Pro 84.7%, o3 84.4%.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen3.5 397B-A17B yet, so there is no like-for-like coding score. On overall capability, o3 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?

Gemini 2.5 Pro has the largest context window at 1,048,576 tokens, against 262,144 for Qwen3.5 397B-A17B and 200,000 for o3. Maximum output per response: Gemini 2.5 Pro up to 65,536, Qwen3.5 397B-A17B up to 65,536, o3 up to 100,000 tokens.

Which can read images, PDFs, audio or video?

Gemini 2.5 Pro accepts text, images, PDFs, audio and video; Qwen3.5 397B-A17B accepts text, images, audio and video; o3 accepts text, images and PDFs. Gemini 2.5 Pro handles the widest range of inputs.

Are any of these open source?

Qwen3.5 397B-A17B publishes its weights and can be self-hosted; Gemini 2.5 Pro and o3 is proprietary.

Which is newer?

Qwen3.5 397B-A17B is the newest, released Feb 15, 2026. Gemini 2.5 Pro came out Jun 17, 2025; o3 came out Apr 16, 2025. Knowledge cutoff: Gemini 2.5 Pro Jan 2025, o3 May 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.