ZMIME
Comparison · 3 models · Updated Oct 4, 2026

Nemotron Mini 4B Instruct vs Llama 3.1 Nemotron Ultra 253B vs GLM-4.5-Flash

Too close to call on our weighted score (GLM-4.5-Flash 65, Llama 3.1 Nemotron Ultra 253B 65, Nemotron Mini 4B Instruct 62). The right pick depends on what you value most.

  1. NVIDIA

    Nemotron Mini 4B Instruct

    Released Aug 21, 2024Deprecated

    62/100
    • ECI—
    • PriceFree / Free
    • Context128K
    Full specs Remove Nemotron Mini 4B Instruct

  2. 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

  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

Too close to call

It is close. Our weighted score puts them within a point (GLM-4.5-Flash 65/100, Llama 3.1 Nemotron Ultra 253B 65/100, Nemotron Mini 4B Instruct 62/100), so choose by what matters most for your work: Nemotron Mini 4B Instruct on price and GLM-4.5-Flash for long inputs. 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 priceSame priceNemotron Mini 4B Instruct Free · Llama 3.1 Nemotron Ultra 253B Free · GLM-4.5-Flash Free per 1M tokens (3:1 blend)
  • Longest contextGLM-4.5-FlashGLM-4.5-Flash 131,072 · Nemotron Mini 4B Instruct 128,000 · Llama 3.1 Nemotron Ultra 253B 128,000 tokens
  • Widest inputsSame inputsNemotron Mini 4B Instruct: Text · Llama 3.1 Nemotron Ultra 253B: Text · GLM-4.5-Flash: Text
  • Self-hostingNemotron Mini 4B Instruct and Llama 3.1 Nemotron Ultra 253BPublishes downloadable weights
How the score is built
MeasureWeightNemotron Mini 4B InstructLlama 3.1 Nemotron Ultra 253BGLM-4.5-Flash
Price50%100100100
Inputs & features30%253535
Context window20%242424
Overall100%62/10065/10065/100

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.

Nemotron Mini 4B Instruct vs Llama 3.1 Nemotron Ultra 253B vs GLM-4.5-Flash specifications side by side
SpecificationNemotron Mini 4B InstructNVIDIALlama 3.1 Nemotron Ultra 253BNVIDIAGLM-4.5-FlashZ.ai (Zhipu)
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
InputFreeFreeFree
OutputFreeFreeFree
Cached input———
Blended (3:1)FreeFreeFree
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Nvidia APIOfficial Nvidia APIOfficial Z.AI API
Limits
Context window128,000 tokens128,000 tokens131,072 tokens (best)
Max output8,192 tokens8,192 tokens98,304 tokens (best)
Inputs and features
TextYesYesYes
ImagesNoNoNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoYesYes
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsOpenOpenProprietary
API model IDnvidia/nemotron-mini-4b-instructnvidia/llama-3.1-nemotron-ultra-253b-v1glm-4.5-flash
API providers114 (best)
ReleasedAug 21, 2024Apr 7, 2025Jul 28, 2025
Knowledge cutoff——Apr 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.

  • Nemotron Mini 4B InstructFree
  • Llama 3.1 Nemotron Ultra 253BFree
  • GLM-4.5-FlashFree
04 — Questions

Which should you choose?

Which is better: Nemotron Mini 4B Instruct, Llama 3.1 Nemotron Ultra 253B or GLM-4.5-Flash?

It is close. Our weighted score puts them within a point (GLM-4.5-Flash 65/100, Llama 3.1 Nemotron Ultra 253B 65/100, Nemotron Mini 4B Instruct 62/100), so choose by what matters most for your work: Nemotron Mini 4B Instruct on price and GLM-4.5-Flash for long inputs. 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, Nemotron Mini 4B Instruct, Llama 3.1 Nemotron Ultra 253B or GLM-4.5-Flash?

Nemotron Mini 4B Instruct, Llama 3.1 Nemotron Ultra 253B and GLM-4.5-Flash cost the same: Free input / Free output per million tokens.

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. Nemotron Mini 4B Instruct has not been scored yet, Llama 3.1 Nemotron Ultra 253B has not been scored yet and GLM-4.5-Flash has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Nemotron Mini 4B Instruct, Llama 3.1 Nemotron Ultra 253B 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?

GLM-4.5-Flash has the largest context window at 131,072 tokens, against 128,000 for Nemotron Mini 4B Instruct and 128,000 for Llama 3.1 Nemotron Ultra 253B. Maximum output per response: Nemotron Mini 4B Instruct up to 8,192, Llama 3.1 Nemotron Ultra 253B up to 8,192, GLM-4.5-Flash up to 98,304 tokens.

Which can read images, PDFs, audio or video?

Nemotron Mini 4B Instruct accepts text; Llama 3.1 Nemotron Ultra 253B accepts text; GLM-4.5-Flash accepts text. They handle the same number of input types.

Are any of these open source?

Nemotron Mini 4B Instruct and Llama 3.1 Nemotron Ultra 253B publishes its weights and can be self-hosted; GLM-4.5-Flash is proprietary.

Which is newer?

GLM-4.5-Flash is the newest, released Jul 28, 2025. Llama 3.1 Nemotron Ultra 253B came out Apr 7, 2025; Nemotron Mini 4B Instruct came out Aug 21, 2024. Knowledge cutoff: 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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