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Comparison · 2 models · Updated Oct 4, 2026

Qwen2.5-Coder-32B-Instruct vs Llama 3.1 Nemotron 70B Instruct

Too close to call on our weighted score (Qwen2.5-Coder-32B-Instruct 45, Llama 3.1 Nemotron 70B Instruct 45). The right pick depends on what you value most.

  1. Alibaba (Qwen)

    Qwen2.5-Coder-32B-Instruct

    Released Nov 12, 2024

    45/100
    • ECI—
    • Price$0.43 / $0.60
    • Context131K
    Full specs Remove Qwen2.5-Coder-32B-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. Add a model

    Make it a three-way comparison.

01 — Verdict

Too close to call

It is close. Our weighted score puts them within a point (Qwen2.5-Coder-32B-Instruct 45/100, Llama 3.1 Nemotron 70B Instruct 45/100), so choose by what matters most for your work: Qwen2.5-Coder-32B-Instruct on price and Qwen2.5-Coder-32B-Instruct 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 priceQwen2.5-Coder-32B-InstructQwen2.5-Coder-32B-Instruct $0.473 · Llama 3.1 Nemotron 70B Instruct $0.485 per 1M tokens (3:1 blend)
  • Longest contextQwen2.5-Coder-32B-InstructQwen2.5-Coder-32B-Instruct 131,072 · Llama 3.1 Nemotron 70B Instruct 128,000 tokens
  • Widest inputsSame inputsQwen2.5-Coder-32B-Instruct: Text · Llama 3.1 Nemotron 70B Instruct: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightQwen2.5-Coder-32B-InstructLlama 3.1 Nemotron 70B Instruct
Price50%6565
Inputs & features30%2525
Context window20%2424
Overall100%45/10045/100

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.

Qwen2.5-Coder-32B-Instruct vs Llama 3.1 Nemotron 70B Instruct specifications side by side
SpecificationQwen2.5-Coder-32B-InstructAlibaba (Qwen)Llama 3.1 Nemotron 70B InstructNVIDIA
Capability
Capabilities Index (ECI)——
ECI rank——
Price per million tokens
Input$0.43 (best)$0.478
Output$0.60$0.504 (best)
Cached input——
Blended (3:1)$0.473 (best)$0.485
Long-context rateSame rateSame rate
Price sourceMedian of 4 providersMedian of 2 providers
Limits
Context window131,072 tokens (best)128,000 tokens
Max output8,192 tokens8,192 tokens
Inputs and features
TextYesYes
ImagesNoNo
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningNoNo
Tool callingYesYes
Structured outputNoNo
Availability
WeightsOpenOpen
API model ID—nvidia/llama-3.1-nemotron-70b-instruct
API providers4 (best)3
ReleasedNov 12, 2024Apr 15, 2025
Knowledge cutoff——
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.

  • Qwen2.5-Coder-32B-Instruct$5.50
  • Llama 3.1 Nemotron 70B Instruct$5.79
04 — Questions

Which should you choose?

Which is better: Qwen2.5-Coder-32B-Instruct or Llama 3.1 Nemotron 70B Instruct?

It is close. Our weighted score puts them within a point (Qwen2.5-Coder-32B-Instruct 45/100, Llama 3.1 Nemotron 70B Instruct 45/100), so choose by what matters most for your work: Qwen2.5-Coder-32B-Instruct on price and Qwen2.5-Coder-32B-Instruct 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, Qwen2.5-Coder-32B-Instruct or Llama 3.1 Nemotron 70B Instruct?

Qwen2.5-Coder-32B-Instruct is cheaper at $0.43 input / $0.60 output per million tokens (median across 4 API providers). Llama 3.1 Nemotron 70B Instruct costs $0.478 input / $0.504 output per million tokens (median across 2 API providers; free on Nvidia). At a typical mix of three input tokens to one output token, that is $0.473 per million tokens for Qwen2.5-Coder-32B-Instruct versus $0.485 for Llama 3.1 Nemotron 70B Instruct (1× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers both models yet. Qwen2.5-Coder-32B-Instruct has not been scored yet and Llama 3.1 Nemotron 70B Instruct has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen2.5-Coder-32B-Instruct and Llama 3.1 Nemotron 70B Instruct yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.

Which has the bigger context window?

Qwen2.5-Coder-32B-Instruct has the largest context window at 131,072 tokens, against 128,000 for Llama 3.1 Nemotron 70B Instruct. Maximum output per response: Qwen2.5-Coder-32B-Instruct up to 8,192, Llama 3.1 Nemotron 70B Instruct up to 8,192 tokens.

Which can read images, PDFs, audio or video?

Qwen2.5-Coder-32B-Instruct accepts text; Llama 3.1 Nemotron 70B Instruct accepts text. They handle the same number of input types.

Are any of these open source?

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

Which is newer?

Llama 3.1 Nemotron 70B Instruct is the newest, released Apr 15, 2025. Qwen2.5-Coder-32B-Instruct came out Nov 12, 2024.

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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