ZMIME
Comparison · 3 models · Updated Nov 2, 2026

GLM-4.5-Air vs GLM-4.7 vs Llama 3.3 Nemotron Super 49B v1.5

Too close to call on our weighted score (Llama 3.3 Nemotron Super 49B v1.5 48, GLM-4.5-Air 48, GLM-4.7 41). The right pick depends on what you value most.

  1. Z.ai (Zhipu)

    GLM-4.5-Air

    Released Jul 28, 2025

    48/100
    • ECI—
    • Price$0.20 / $1.10
    • Context131K
    Full specs Remove GLM-4.5-Air

  2. Z.ai (Zhipu)

    GLM-4.7

    Released Dec 22, 2025

    41/100
    • ECI143.7
    • Price$0.60 / $2.20
    • Context205K
    Full specs Remove GLM-4.7

  3. NVIDIA

    Llama 3.3 Nemotron Super 49B v1.5

    Released Jul 25, 2025

    48/100
    • ECI—
    • Price$0.40 / $0.40
    • Context131K
    Full specs Remove Llama 3.3 Nemotron Super 49B v1.5
01 — Verdict

Too close to call

It is close. Our weighted score puts them within a point (Llama 3.3 Nemotron Super 49B v1.5 48/100, GLM-4.5-Air 48/100, GLM-4.7 41/100), so choose by what matters most for your work: Llama 3.3 Nemotron Super 49B v1.5 on price and GLM-4.7 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 priceLlama 3.3 Nemotron Super 49B v1.5Llama 3.3 Nemotron Super 49B v1.5 $0.40 · GLM-4.5-Air $0.425 · GLM-4.7 $1.00 per 1M tokens (3:1 blend)
  • Longest contextGLM-4.7GLM-4.7 204,800 · GLM-4.5-Air 131,072 · Llama 3.3 Nemotron Super 49B v1.5 131,072 tokens
  • Widest inputsSame inputsGLM-4.5-Air: Text · GLM-4.7: Text · Llama 3.3 Nemotron Super 49B v1.5: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightGLM-4.5-AirGLM-4.7Llama 3.3 Nemotron Super 49B v1.5
Price50%654866
Inputs & features30%353535
Context window20%253225
Overall100%48/10041/10048/100

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-Air vs GLM-4.7 vs Llama 3.3 Nemotron Super 49B v1.5 specifications side by side
SpecificationGLM-4.5-AirZ.ai (Zhipu)GLM-4.7Z.ai (Zhipu)Llama 3.3 Nemotron Super 49B v1.5NVIDIA
Capability
Capabilities Index (ECI)—143.7—
ECI rank—#94 of 165—
GPQA DiamondGraduate-level science questions—83.3%—
OTIS Mock AIME 2024–2025Competition mathematics—83.3%—
SimpleQA VerifiedShort factual questions—32.2%—
Price per million tokens
Input$0.20 (best)$0.60$0.40
Output$1.10$2.20$0.40 (best)
Cached input$0.03 (best)$0.11—
Blended (3:1)$0.425$1.00$0.40 (best)
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Z.AI APIOfficial Z.AI APIMedian of 1 providers
Limits
Context window131,072 tokens204,800 tokens (best)131,072 tokens
Max output98,304 tokens131,072 tokens (best)131,072 tokens (best)
Inputs and features
TextYesYesYes
ImagesNoNoNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningYesYesYes
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsOpenOpenOpen
API model IDglm-4.5-airglm-4.7—
API providers1931 (best)1
ReleasedJul 28, 2025Dec 22, 2025Jul 25, 2025
Knowledge cutoffApr 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.

  • GLM-4.5-Air$4.20
  • GLM-4.7$10.40
  • Llama 3.3 Nemotron Super 49B v1.5$4.80
04 — Questions

Which should you choose?

Which is better: GLM-4.5-Air, GLM-4.7 or Llama 3.3 Nemotron Super 49B v1.5?

It is close. Our weighted score puts them within a point (Llama 3.3 Nemotron Super 49B v1.5 48/100, GLM-4.5-Air 48/100, GLM-4.7 41/100), so choose by what matters most for your work: Llama 3.3 Nemotron Super 49B v1.5 on price and GLM-4.7 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, GLM-4.5-Air, GLM-4.7 or Llama 3.3 Nemotron Super 49B v1.5?

Llama 3.3 Nemotron Super 49B v1.5 is cheaper at $0.40 input / $0.40 output per million tokens (median across 1 API provider). GLM-4.5-Air costs $0.20 input / $1.10 output per million tokens (official Z.AI API price); GLM-4.7 costs $0.60 input / $2.20 output per million tokens (official Z.AI API price). At a typical mix of three input tokens to one output token, that is $0.40 per million tokens for Llama 3.3 Nemotron Super 49B v1.5 versus $0.425 for GLM-4.5-Air (1.1× as much) and $1.00 for GLM-4.7 (2.5× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. GLM-4.5-Air has not been scored yet, GLM-4.7 has an ECI of 143.7 and Llama 3.3 Nemotron Super 49B v1.5 has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for GLM-4.5-Air, GLM-4.7 and Llama 3.3 Nemotron Super 49B v1.5 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-4.7 has the largest context window at 204,800 tokens, against 131,072 for GLM-4.5-Air and 131,072 for Llama 3.3 Nemotron Super 49B v1.5. Maximum output per response: GLM-4.5-Air up to 98,304, GLM-4.7 up to 131,072, Llama 3.3 Nemotron Super 49B v1.5 up to 131,072 tokens.

Which can read images, PDFs, audio or video?

GLM-4.5-Air accepts text; GLM-4.7 accepts text; Llama 3.3 Nemotron Super 49B v1.5 accepts text. They handle the same number of input types.

Are any of these open source?

Yes, all three publish their weights, so you can self-host them.

Which is newer?

GLM-4.7 is the newest, released Dec 22, 2025. GLM-4.5-Air came out Jul 28, 2025; Llama 3.3 Nemotron Super 49B v1.5 came out Jul 25, 2025. Knowledge cutoff: GLM-4.5-Air Apr 2025, GLM-4.7 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 Nov 2, 2026.

05 — Keep comparing

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