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Comparison · 3 models · Updated Oct 4, 2026

Qwen3-Next 80B-A3B Instruct vs Llama 3.1 Nemotron 70B Instruct vs GLM-4.5V

GLM-4.5V comes out ahead, 49 to 45 and 39 on our weighted score, though Llama 3.1 Nemotron 70B Instruct is 46% cheaper per token.

  1. Alibaba (Qwen)

    Qwen3-Next 80B-A3B Instruct

    Released Sep 2025

    39/100
    • ECI—
    • Price$0.50 / $2.00
    • Context131K
    Full specs Remove Qwen3-Next 80B-A3B Instruct

  2. NVIDIA

    Llama 3.1 Nemotron 70B Instruct

    Released Apr 15, 2025

    45/100
    • ECI—
    • Price$0.478 / $0.504
    • Context128K
    Full specs Remove Llama 3.1 Nemotron 70B Instruct
  3. Our pick

    Z.ai (Zhipu)

    GLM-4.5V

    Released Aug 11, 2025

    49/100
    • ECI—
    • Price$0.60 / $1.80
    • Context64K
    Full specs Remove GLM-4.5V
01 — Verdict

GLM-4.5V is our pick

GLM-4.5V is the better all-round choice, scoring 49/100 against Llama 3.1 Nemotron 70B Instruct (45) and Qwen3-Next 80B-A3B Instruct (39). It leads on inputs & features. Llama 3.1 Nemotron 70B Instruct wins 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 priceLlama 3.1 Nemotron 70B InstructLlama 3.1 Nemotron 70B Instruct $0.485 · Qwen3-Next 80B-A3B Instruct $0.875 · GLM-4.5V $0.90 per 1M tokens (3:1 blend)
  • Longest contextQwen3-Next 80B-A3B InstructQwen3-Next 80B-A3B Instruct 131,072 · Llama 3.1 Nemotron 70B Instruct 128,000 · GLM-4.5V 64,000 tokens
  • Widest inputsGLM-4.5VQwen3-Next 80B-A3B Instruct: Text · Llama 3.1 Nemotron 70B Instruct: Text · GLM-4.5V: Text, Images, Video
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightQwen3-Next 80B-A3B InstructLlama 3.1 Nemotron 70B InstructGLM-4.5V
Price50%536552
Inputs & features30%252570
Context window20%242412
Overall100%39/10045/10049/100

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.

Qwen3-Next 80B-A3B Instruct vs Llama 3.1 Nemotron 70B Instruct vs GLM-4.5V specifications side by side
SpecificationQwen3-Next 80B-A3B InstructAlibaba (Qwen)Llama 3.1 Nemotron 70B InstructNVIDIAGLM-4.5VZ.ai (Zhipu)
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
Input$0.50$0.478 (best)$0.60
Output$2.00$0.504 (best)$1.80
Cached input———
Blended (3:1)$0.875$0.485 (best)$0.90
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Alibaba APIMedian of 2 providersOfficial Z.AI API
Limits
Context window131,072 tokens (best)128,000 tokens64,000 tokens
Max output32,768 tokens (best)8,192 tokens16,384 tokens
Inputs and features
TextYesYesYes
ImagesNoNoYes
PDFsNoNoNo
AudioNoNoNo
VideoNoNoYes
ReasoningNoNoYes
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsOpenOpenOpen
API model IDqwen3-next-80b-a3b-instructnvidia/llama-3.1-nemotron-70b-instructglm-4.5v
API providers13 (best)311
ReleasedSep 2025Apr 15, 2025Aug 11, 2025
Knowledge cutoffApr 2025—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.

  • Qwen3-Next 80B-A3B Instruct$9.00
  • Llama 3.1 Nemotron 70B Instruct$5.79
  • GLM-4.5V$9.60
04 — Questions

Which should you choose?

Which is better: Qwen3-Next 80B-A3B Instruct, Llama 3.1 Nemotron 70B Instruct or GLM-4.5V?

GLM-4.5V is the better all-round choice, scoring 49/100 against Llama 3.1 Nemotron 70B Instruct (45) and Qwen3-Next 80B-A3B Instruct (39). It leads on inputs & features. Llama 3.1 Nemotron 70B Instruct wins 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, Qwen3-Next 80B-A3B Instruct, Llama 3.1 Nemotron 70B Instruct or GLM-4.5V?

Llama 3.1 Nemotron 70B Instruct is cheaper at $0.478 input / $0.504 output per million tokens (median across 2 API providers; free on Nvidia). Qwen3-Next 80B-A3B Instruct costs $0.50 input / $2.00 output per million tokens (official Alibaba API price); GLM-4.5V costs $0.60 input / $1.80 output per million tokens (official Z.AI API price). At a typical mix of three input tokens to one output token, that is $0.485 per million tokens for Llama 3.1 Nemotron 70B Instruct versus $0.875 for Qwen3-Next 80B-A3B Instruct (1.8× as much) and $0.90 for GLM-4.5V (1.9× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. Qwen3-Next 80B-A3B Instruct has not been scored yet, Llama 3.1 Nemotron 70B Instruct has not been scored yet and GLM-4.5V has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen3-Next 80B-A3B Instruct, Llama 3.1 Nemotron 70B Instruct and GLM-4.5V 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?

Qwen3-Next 80B-A3B Instruct has the largest context window at 131,072 tokens, against 128,000 for Llama 3.1 Nemotron 70B Instruct and 64,000 for GLM-4.5V. Maximum output per response: Qwen3-Next 80B-A3B Instruct up to 32,768, Llama 3.1 Nemotron 70B Instruct up to 8,192, GLM-4.5V up to 16,384 tokens.

Which can read images, PDFs, audio or video?

Qwen3-Next 80B-A3B Instruct accepts text; Llama 3.1 Nemotron 70B Instruct accepts text; GLM-4.5V accepts text, images and video. GLM-4.5V handles the widest range of inputs.

Are any of these open source?

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

Which is newer?

Qwen3-Next 80B-A3B Instruct is the newest, released Sep 2025. GLM-4.5V came out Aug 11, 2025; Llama 3.1 Nemotron 70B Instruct came out Apr 15, 2025. Knowledge cutoff: Qwen3-Next 80B-A3B Instruct Apr 2025, GLM-4.5V 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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