ZMIME
Comparison · 3 models · Updated Oct 4, 2026

GLM-4.5-Flash vs Mistral Nemotron vs Nemotron Nano 9B v2

Too close to call on our weighted score (GLM-4.5-Flash 65, Nemotron Nano 9B v2 64, Mistral Nemotron 62). The right pick depends on what you value most.

  1. Z.ai (Zhipu)

    GLM-4.5-Flash

    Released Jul 28, 2025

    65/100
    • ECI—
    • PriceFree / Free
    • Context131K
  2. NVIDIA

    Mistral Nemotron

    Released Jun 11, 2025Deprecated

    62/100
    • ECI—
    • PriceFree / Free
    • Context128K
  3. NVIDIA

    Nemotron Nano 9B v2

    Released Aug 18, 2025Deprecated

    64/100
    • ECI—
    • Price$0.06 / $0.23
    • Context131K
01 — Verdict

Too close to call

It is close. Our weighted score puts them within 2 points (GLM-4.5-Flash 65/100, Nemotron Nano 9B v2 64/100, Mistral Nemotron 62/100), so choose by what matters most for your work: GLM-4.5-Flash on price. 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 priceGLM-4.5-Flash and Mistral NemotronGLM-4.5-Flash Free · Mistral Nemotron Free · Nemotron Nano 9B v2 $0.102 per 1M tokens (3:1 blend)
  • Longest contextGLM-4.5-Flash and Nemotron Nano 9B v2GLM-4.5-Flash 131,072 · Nemotron Nano 9B v2 131,072 · Mistral Nemotron 128,000 tokens
  • Widest inputsSame inputsGLM-4.5-Flash: Text · Mistral Nemotron: Text · Nemotron Nano 9B v2: Text
  • Self-hostingMistral Nemotron and Nemotron Nano 9B v2Publishes downloadable weights
How the score is built
MeasureWeightGLM-4.5-FlashMistral NemotronNemotron Nano 9B v2
Price50%10010097
Inputs & features30%352535
Context window20%242424
Overall100%65/10062/10064/100

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.

GLM-4.5-Flash vs Mistral Nemotron vs Nemotron Nano 9B v2 specifications side by side
SpecificationGLM-4.5-FlashZ.ai (Zhipu)Mistral NemotronNVIDIANemotron Nano 9B v2NVIDIA
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
InputFree (best)Free (best)$0.06
OutputFree (best)Free (best)$0.23
Cached input———
Blended (3:1)Free (best)Free (best)$0.102
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Z.AI APIOfficial Nvidia APIMedian of 3 providers
Limits
Context window131,072 tokens (best)128,000 tokens131,072 tokens (best)
Max output98,304 tokens8,192 tokens131,072 tokens (best)
Inputs and features
TextYesYesYes
ImagesNoNoNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningYesNoYes
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsProprietaryOpenOpen
API model IDglm-4.5-flashmistralai/mistral-nemotronnvidia/nvidia-nemotron-nano-9b-v2
API providers4 (best)14 (best)
ReleasedJul 28, 2025Jun 11, 2025Aug 18, 2025
Knowledge cutoffApr 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.

  • GLM-4.5-FlashFree
  • Mistral NemotronFree
  • Nemotron Nano 9B v2$1.06
04 — Questions

Which should you choose?

Which is better: GLM-4.5-Flash, Mistral Nemotron or Nemotron Nano 9B v2?

It is close. Our weighted score puts them within 2 points (GLM-4.5-Flash 65/100, Nemotron Nano 9B v2 64/100, Mistral Nemotron 62/100), so choose by what matters most for your work: GLM-4.5-Flash on price. 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, GLM-4.5-Flash, Mistral Nemotron or Nemotron Nano 9B v2?

GLM-4.5-Flash is cheaper at Free input / Free output per million tokens (official Z.AI API price). Mistral Nemotron costs Free input / Free output per million tokens (official Nvidia API price); Nemotron Nano 9B v2 costs $0.06 input / $0.23 output per million tokens (median across 3 API providers; free on Nvidia). GLM-4.5-Flash is listed as free.

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. GLM-4.5-Flash has not been scored yet, Mistral Nemotron has not been scored yet and Nemotron Nano 9B v2 has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for GLM-4.5-Flash, Mistral Nemotron and Nemotron Nano 9B v2 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 and Nemotron Nano 9B v2 have the largest context windows (131,072 and 131,072 tokens), against 128,000 for Mistral Nemotron. Maximum output per response: GLM-4.5-Flash up to 98,304, Mistral Nemotron up to 8,192, Nemotron Nano 9B v2 up to 131,072 tokens.

Which can read images, PDFs, audio or video?

GLM-4.5-Flash accepts text; Mistral Nemotron accepts text; Nemotron Nano 9B v2 accepts text. They handle the same number of input types.

Are any of these open source?

Mistral Nemotron and Nemotron Nano 9B v2 publishes its weights and can be self-hosted; GLM-4.5-Flash is proprietary.

Which is newer?

Nemotron Nano 9B v2 is the newest, released Aug 18, 2025. GLM-4.5-Flash came out Jul 28, 2025; Mistral Nemotron came out Jun 11, 2025. 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.