ZMIME
Comparison · 3 models · Updated Oct 4, 2026

Gemini 2.5 Flash-Lite vs GPT-5 Nano vs Qwen3.5 9B

Too close to call on our weighted score (Qwen3.5 9B 72, Gemini 2.5 Flash-Lite 71, GPT-5 Nano 70). The right pick depends on what you value most.

  1. Google

    Gemini 2.5 Flash-Lite

    Released Jun 17, 2025

    71/100
    • ECI133.9
    • Price$0.10 / $0.40
    • Context1.05M
    Full specs Remove Gemini 2.5 Flash-Lite

  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 a point (Qwen3.5 9B 72/100, Gemini 2.5 Flash-Lite 71/100, GPT-5 Nano 70/100), so choose by what matters most for your work: Qwen3.5 9B for raw capability and Gemini 2.5 Flash-Lite 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 · Gemini 2.5 Flash-Lite 133.9
  • Lowest priceQwen3.5 9BQwen3.5 9B $0.113 · GPT-5 Nano $0.138 · Gemini 2.5 Flash-Lite $0.175 per 1M tokens (3:1 blend)
  • Longest contextGemini 2.5 Flash-LiteGemini 2.5 Flash-Lite 1,048,576 · GPT-5 Nano 400,000 · Qwen3.5 9B 262,144 tokens
  • Widest inputsGemini 2.5 Flash-LiteGemini 2.5 Flash-Lite: Text, Images, PDFs, Audio, Video · GPT-5 Nano: Text, Images · Qwen3.5 9B: Text, Images, Video
  • Self-hostingQwen3.5 9BPublishes downloadable weights
How the score is built
MeasureWeightGemini 2.5 Flash-LiteGPT-5 NanoQwen3.5 9B
CapabilityCapabilities Index (ECI)50%586565
Price25%869195
Inputs & features15%1007080
Context window10%614437
Overall100%71/10070/10072/100
02 — Side by side

Every spec in one table

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

Gemini 2.5 Flash-Lite vs GPT-5 Nano vs Qwen3.5 9B specifications side by side
SpecificationGemini 2.5 Flash-LiteGoogleGPT-5 NanoOpenAIQwen3.5 9BAlibaba (Qwen)
Capability
Capabilities Index (ECI)133.9139.4139.5 (best)
ECI rank#118 of 148#102 of 148#101 of 148 (best)
GPQA DiamondGraduate-level science questions—69.4%79.0% (best)
FrontierMath Tiers 1–3Research-level mathematics—20.0%—
OTIS Mock AIME 2024–2025Competition mathematics—81.1% (best)61.7%
SimpleQA VerifiedShort factual questions—11.7%—
Price per million tokens
Input$0.10$0.05 (best)$0.10
Output$0.40$0.40$0.15 (best)
Cached input$0.01$0.005 (best)—
Blended (3:1)$0.175$0.138$0.113 (best)
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Google APIOfficial OpenAI APIMedian of 14 providers
Limits
Context window1,048,576 tokens (best)400,000 tokens262,144 tokens
Max output65,536 tokens128,000 tokens (best)65,536 tokens
Inputs and features
TextYesYesYes
ImagesYesYesYes
PDFsYesNoNo
AudioYesNoNo
VideoYesNoYes
ReasoningYesYesminimal · low · medium · highYes
Tool callingYesYesYes
Structured outputYesYesYes
Availability
WeightsProprietaryProprietaryOpen
API model IDgemini-2.5-flash-litegpt-5-nano—
API providers2021 (best)15
ReleasedJun 17, 2025Aug 7, 2025Feb 23, 2026
Knowledge cutoffJan 2025May 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 Flash-Lite$1.80
  • GPT-5 Nano$1.30
  • Qwen3.5 9B$1.30
04 — Questions

Which should you choose?

Which is better: Gemini 2.5 Flash-Lite, GPT-5 Nano or Qwen3.5 9B?

It is close. Our weighted score puts them within a point (Qwen3.5 9B 72/100, Gemini 2.5 Flash-Lite 71/100, GPT-5 Nano 70/100), so choose by what matters most for your work: Qwen3.5 9B for raw capability and Gemini 2.5 Flash-Lite for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Gemini 2.5 Flash-Lite, GPT-5 Nano or Qwen3.5 9B?

Qwen3.5 9B is cheaper at $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); Gemini 2.5 Flash-Lite costs $0.10 input / $0.40 output per million tokens (official Google API price). At a typical mix of three input tokens to one output token, that is $0.113 per million tokens for Qwen3.5 9B versus $0.138 for GPT-5 Nano (1.2× as much) and $0.175 for Gemini 2.5 Flash-Lite (1.6× 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 Gemini 2.5 Flash-Lite 133.9 (#118 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.

Which is better for coding?

There are no published SWE-bench Verified results for Gemini 2.5 Flash-Lite, 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?

Gemini 2.5 Flash-Lite has the largest context window at 1,048,576 tokens, against 400,000 for GPT-5 Nano and 262,144 for Qwen3.5 9B. Maximum output per response: Gemini 2.5 Flash-Lite up to 65,536, GPT-5 Nano up to 128,000, Qwen3.5 9B up to 65,536 tokens.

Which can read images, PDFs, audio or video?

Gemini 2.5 Flash-Lite accepts text, images, PDFs, audio and video; GPT-5 Nano accepts text and images; Qwen3.5 9B accepts text, images and video. Gemini 2.5 Flash-Lite handles the widest range of inputs.

Are any of these open source?

Qwen3.5 9B publishes its weights and can be self-hosted; Gemini 2.5 Flash-Lite and 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; Gemini 2.5 Flash-Lite came out Jun 17, 2025. Knowledge cutoff: Gemini 2.5 Flash-Lite Jan 2025, 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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