ZMIME
Comparison · 3 models · Updated Oct 4, 2026

Llama 3.1 Nemotron Ultra 253B vs Gemini 2.5 Flash-Lite vs GLM-4.5-Flash

Gemini 2.5 Flash-Lite comes out ahead, 85 to 65 and 65 on our weighted score.

  1. NVIDIA

    Llama 3.1 Nemotron Ultra 253B

    Released Apr 7, 2025

    65/100
    • ECI—
    • PriceFree / Free
    • Context128K
    Full specs Remove Llama 3.1 Nemotron Ultra 253B
  2. Our pick

    Google

    Gemini 2.5 Flash-Lite

    Released Jun 17, 2025

    85/100
    • ECI133.9
    • Price$0.10 / $0.40
    • Context1.05M
    Full specs Remove Gemini 2.5 Flash-Lite

  3. Z.ai (Zhipu)

    GLM-4.5-Flash

    Released Jul 28, 2025

    65/100
    • ECI—
    • PriceFree / Free
    • Context131K
    Full specs Remove GLM-4.5-Flash
01 — Verdict

Gemini 2.5 Flash-Lite is our pick

Gemini 2.5 Flash-Lite is the better all-round choice, scoring 85/100 against GLM-4.5-Flash (65) and Llama 3.1 Nemotron Ultra 253B (65). It leads 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 priceLlama 3.1 Nemotron Ultra 253B and GLM-4.5-FlashLlama 3.1 Nemotron Ultra 253B Free · GLM-4.5-Flash Free · 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 · GLM-4.5-Flash 131,072 · Llama 3.1 Nemotron Ultra 253B 128,000 tokens
  • Widest inputsGemini 2.5 Flash-LiteLlama 3.1 Nemotron Ultra 253B: Text · Gemini 2.5 Flash-Lite: Text, Images, PDFs, Audio, Video · GLM-4.5-Flash: Text
  • Self-hostingLlama 3.1 Nemotron Ultra 253BPublishes downloadable weights
How the score is built
MeasureWeightLlama 3.1 Nemotron Ultra 253BGemini 2.5 Flash-LiteGLM-4.5-Flash
Price50%10086100
Inputs & features30%3510035
Context window20%246124
Overall100%65/10085/10065/100

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.

Llama 3.1 Nemotron Ultra 253B vs Gemini 2.5 Flash-Lite vs GLM-4.5-Flash specifications side by side
SpecificationLlama 3.1 Nemotron Ultra 253BNVIDIAGemini 2.5 Flash-LiteGoogleGLM-4.5-FlashZ.ai (Zhipu)
Capability
Capabilities Index (ECI)—133.9—
ECI rank—#118 of 148—
Price per million tokens
InputFree (best)$0.10Free (best)
OutputFree (best)$0.40Free (best)
Cached input—$0.01—
Blended (3:1)Free (best)$0.175Free (best)
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Nvidia APIOfficial Google APIOfficial Z.AI API
Limits
Context window128,000 tokens1,048,576 tokens (best)131,072 tokens
Max output8,192 tokens65,536 tokens98,304 tokens (best)
Inputs and features
TextYesYesYes
ImagesNoYesNo
PDFsNoYesNo
AudioNoYesNo
VideoNoYesNo
ReasoningYesYesYes
Tool callingYesYesYes
Structured outputNoYesNo
Availability
WeightsOpenProprietaryProprietary
API model IDnvidia/llama-3.1-nemotron-ultra-253b-v1gemini-2.5-flash-liteglm-4.5-flash
API providers120 (best)4
ReleasedApr 7, 2025Jun 17, 2025Jul 28, 2025
Knowledge cutoff—Jan 2025Apr 2025
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.

  • Llama 3.1 Nemotron Ultra 253BFree
  • Gemini 2.5 Flash-Lite$1.80
  • GLM-4.5-FlashFree
04 — Questions

Which should you choose?

Which is better: Llama 3.1 Nemotron Ultra 253B, Gemini 2.5 Flash-Lite or GLM-4.5-Flash?

Gemini 2.5 Flash-Lite is the better all-round choice, scoring 85/100 against GLM-4.5-Flash (65) and Llama 3.1 Nemotron Ultra 253B (65). It leads 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, Llama 3.1 Nemotron Ultra 253B, Gemini 2.5 Flash-Lite or GLM-4.5-Flash?

Llama 3.1 Nemotron Ultra 253B is cheaper at Free input / Free output per million tokens (official Nvidia API price). GLM-4.5-Flash costs Free input / Free output per million tokens (official Z.AI API price); Gemini 2.5 Flash-Lite costs $0.10 input / $0.40 output per million tokens (official Google API price). Llama 3.1 Nemotron Ultra 253B is listed as free.

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. Llama 3.1 Nemotron Ultra 253B has not been scored yet, Gemini 2.5 Flash-Lite has an ECI of 133.9 and GLM-4.5-Flash has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Llama 3.1 Nemotron Ultra 253B, Gemini 2.5 Flash-Lite and GLM-4.5-Flash 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?

Gemini 2.5 Flash-Lite has the largest context window at 1,048,576 tokens, against 131,072 for GLM-4.5-Flash and 128,000 for Llama 3.1 Nemotron Ultra 253B. Maximum output per response: Llama 3.1 Nemotron Ultra 253B up to 8,192, Gemini 2.5 Flash-Lite up to 65,536, GLM-4.5-Flash up to 98,304 tokens.

Which can read images, PDFs, audio or video?

Llama 3.1 Nemotron Ultra 253B accepts text; Gemini 2.5 Flash-Lite accepts text, images, PDFs, audio and video; GLM-4.5-Flash accepts text. Gemini 2.5 Flash-Lite handles the widest range of inputs.

Are any of these open source?

Llama 3.1 Nemotron Ultra 253B publishes its weights and can be self-hosted; Gemini 2.5 Flash-Lite and GLM-4.5-Flash is proprietary.

Which is newer?

GLM-4.5-Flash is the newest, released Jul 28, 2025. Gemini 2.5 Flash-Lite came out Jun 17, 2025; Llama 3.1 Nemotron Ultra 253B came out Apr 7, 2025. Knowledge cutoff: Gemini 2.5 Flash-Lite Jan 2025, GLM-4.5-Flash Apr 2025.

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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