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Comparison · 3 models · Updated Oct 4, 2026

Gemma 3 27B IT vs GPT-5 Nano vs Qwen3.5 9B

Too close to call on our weighted score (Qwen3.5 9B 72, GPT-5 Nano 70, Gemma 3 27B IT 60). The right pick depends on what you value most.

  1. Google

    Gemma 3 27B IT

    Released Mar 12, 2025

    60/100
    • ECI130.0
    • Price$0.08 / $0.20
    • Context131K
    Full specs Remove Gemma 3 27B IT

  2. OpenAI

    GPT-5 Nano

    Released Aug 7, 2025

    70/100
    • ECI139.4
    • Price$0.05 / $0.40
    • Context400K
    Full specs Remove GPT-5 Nano

  3. Alibaba (Qwen)

    Qwen3.5 9B

    Released Feb 23, 2026

    72/100
    • ECI139.5
    • Price$0.10 / $0.15
    • Context262K
    Full specs Remove Qwen3.5 9B
01 — Verdict

Too close to call

It is close. Our weighted score puts them within 2 points (Qwen3.5 9B 72/100, GPT-5 Nano 70/100, Gemma 3 27B IT 60/100), so choose by what matters most for your work: Qwen3.5 9B for raw capability, Gemma 3 27B IT on price and GPT-5 Nano for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityQwen3.5 9BCapabilities Index (ECI): Qwen3.5 9B 139.5 · GPT-5 Nano 139.4 · Gemma 3 27B IT 130.0
  • Lowest priceGemma 3 27B ITGemma 3 27B IT $0.11 · Qwen3.5 9B $0.113 · GPT-5 Nano $0.138 per 1M tokens (3:1 blend)
  • Longest contextGPT-5 NanoGPT-5 Nano 400,000 · Qwen3.5 9B 262,144 · Gemma 3 27B IT 131,072 tokens
  • Widest inputsQwen3.5 9BGemma 3 27B IT: Text, Images · GPT-5 Nano: Text, Images · Qwen3.5 9B: Text, Images, Video
  • Self-hostingGemma 3 27B IT and Qwen3.5 9BPublishes downloadable weights
How the score is built
MeasureWeightGemma 3 27B ITGPT-5 NanoQwen3.5 9B
CapabilityCapabilities Index (ECI)50%536565
Price25%959195
Inputs & features15%507080
Context window10%244437
Overall100%60/10070/10072/100
02 — Side by side

Every spec in one table

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

Gemma 3 27B IT vs GPT-5 Nano vs Qwen3.5 9B specifications side by side
SpecificationGemma 3 27B ITGoogleGPT-5 NanoOpenAIQwen3.5 9BAlibaba (Qwen)
Capability
Capabilities Index (ECI)130.0139.4139.5 (best)
ECI rank#125 of 148#102 of 148#101 of 148 (best)
GPQA DiamondGraduate-level science questions47.7%69.4%79.0% (best)
FrontierMath Tiers 1–3Research-level mathematics—20.0%—
OTIS Mock AIME 2024–2025Competition mathematics22.5%81.1% (best)61.7%
SimpleQA VerifiedShort factual questions—11.7%—
Price per million tokens
Input$0.08$0.05 (best)$0.10
Output$0.20$0.40$0.15 (best)
Cached input—$0.005—
Blended (3:1)$0.11 (best)$0.138$0.113
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 9 providersOfficial OpenAI APIMedian of 14 providers
Limits
Context window131,072 tokens400,000 tokens (best)262,144 tokens
Max output131,072 tokens (best)128,000 tokens65,536 tokens
Inputs and features
TextYesYesYes
ImagesYesYesYes
PDFsNoNoNo
AudioNoNoNo
VideoNoNoYes
ReasoningNoYesminimal · low · medium · highYes
Tool callingYesYesYes
Structured outputNoYesYes
Availability
WeightsOpenProprietaryOpen
API model ID—gpt-5-nano—
API providers1021 (best)15
ReleasedMar 12, 2025Aug 7, 2025Feb 23, 2026
Knowledge cutoffAug 2024May 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.

  • Gemma 3 27B IT$1.20
  • GPT-5 Nano$1.30
  • Qwen3.5 9B$1.30
04 — Questions

Which should you choose?

Which is better: Gemma 3 27B IT, GPT-5 Nano or Qwen3.5 9B?

It is close. Our weighted score puts them within 2 points (Qwen3.5 9B 72/100, GPT-5 Nano 70/100, Gemma 3 27B IT 60/100), so choose by what matters most for your work: Qwen3.5 9B for raw capability, Gemma 3 27B IT on price and GPT-5 Nano for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Gemma 3 27B IT, GPT-5 Nano or Qwen3.5 9B?

Gemma 3 27B IT is cheaper at $0.08 input / $0.20 output per million tokens (median across 9 API providers). Qwen3.5 9B costs $0.10 input / $0.15 output per million tokens (median across 14 API providers); GPT-5 Nano costs $0.05 input / $0.40 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $0.11 per million tokens for Gemma 3 27B IT versus $0.113 for Qwen3.5 9B (1× as much) and $0.138 for GPT-5 Nano (1.3× as much).

Which scores higher on benchmarks?

Qwen3.5 9B scores higher on the Capabilities Index (ECI): Qwen3.5 9B 139.5 (#101 of 148), GPT-5 Nano 139.4 (#102 of 148) and Gemma 3 27B IT 130.0 (#125 of 148). The confidence ranges of the top two overlap (136.5–141.3 vs 134.9–141.7), so treat the gap as small. On individual benchmarks: GPQA Diamond — Qwen3.5 9B 79.0%, GPT-5 Nano 69.4%, Gemma 3 27B IT 47.7%; OTIS Mock AIME 2024–2025 — GPT-5 Nano 81.1%, Qwen3.5 9B 61.7%, Gemma 3 27B IT 22.5%.

Which is better for coding?

There are no published SWE-bench Verified results for Gemma 3 27B IT, GPT-5 Nano and Qwen3.5 9B yet, so there is no like-for-like coding score. On overall capability, Qwen3.5 9B 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-5 Nano has the largest context window at 400,000 tokens, against 262,144 for Qwen3.5 9B and 131,072 for Gemma 3 27B IT. Maximum output per response: Gemma 3 27B IT up to 131,072, GPT-5 Nano up to 128,000, Qwen3.5 9B up to 65,536 tokens.

Which can read images, PDFs, audio or video?

Gemma 3 27B IT accepts text and images; GPT-5 Nano accepts text and images; Qwen3.5 9B accepts text, images and video. Qwen3.5 9B handles the widest range of inputs.

Are any of these open source?

Gemma 3 27B IT and Qwen3.5 9B publishes its weights and can be self-hosted; GPT-5 Nano is proprietary.

Which is newer?

Qwen3.5 9B is the newest, released Feb 23, 2026. GPT-5 Nano came out Aug 7, 2025; Gemma 3 27B IT came out Mar 12, 2025. Knowledge cutoff: Gemma 3 27B IT Aug 2024, GPT-5 Nano May 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.

05 — Keep comparing

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