Llama 3.1 Nemotron 70B Instruct vs Mistral Small

    Comparison

    As of August 30, 2026, Mistral Small is 67% cheaper per million tokens than Llama 3.1 Nemotron 70B Instruct. Llama 3.1 Nemotron 70B Instruct is $1.20 / $1.20 per million input/output tokens versus Mistral Small at $0.20 / $0.60. Sources: https://build.nvidia.com/nvidia/llama-3_1-nemotron-70b-instruct and https://docs.mistral.ai/platform/pricing/

    Sources: NVIDIA pricing (https://build.nvidia.com/nvidia/llama-3_1-nemotron-70b-instruct); Mistral AI pricing (https://docs.mistral.ai/platform/pricing/)

    Llama 3.1 Nemotron 70B Instruct

    NVIDIA

    $2.40blended / 1M

    Input

    $1.20

    Output

    $1.20

    131.1K ctx|Open Source
    67%
    cheaper
    Better value

    Mistral Small

    Mistral

    $0.80blended / 1M

    Input

    $0.20

    Output

    $0.60

    32.8K ctx|Open Source
    Save $1.60 per million tokens by choosing Mistral Small over Llama 3.1 Nemotron 70B Instruct.

    Llama 3.1 Nemotron 70B Instruct vs Mistral Small comparison

    Token pricing, specs, and benchmarks side by side

    Shared benchmarks

    Each bar is share of the current leader on that eval. Click a row to open the board.

    Llama 3.1 Nemotron 70B InstructMistral Small

    Score vs price

    MMLU. Left is cheaper. Up is a higher score. The line is the best score you can buy at each price.

    Best score at each priceLlama 3.1 Nemotron 70B InstructMistral Small
    Metric
    Llama 3.1 Nemotron 70B Instruct
    Mistral Small
    Provider
    Provider
    NVIDIA
    Mistral
    License
    Open Source
    Open Source
    Release Date
    2024-10-01
    2024-09-17
    Pricing (per 1M tokens)
    Input Price+500%
    $1.20
    $0.20
    Output Price+100%
    $1.20
    $0.60
    Blended (1M + 1M)
    $2.40
    $0.80
    Model Details
    Context Window
    131.1K
    32.8K
    Max Output Tokens
    N/A
    32.8K
    Knowledge Cutoff
    2023-12-01
    N/A
    Throughput
    N/A
    0.1 tok/s
    Benchmarks
    80.2%
    68.7%
    85.6%
    69.2%
    91.4%
    81.9%
    80.6%
    9.0%
    58.6%
    84.5%
    Benchmark Wins
    Llama 3.1 Nemotron 70B Instruct 1|0 Mistral Small

    Verdict

    Llama 3.1 Nemotron 70B Instruct vs Mistral Small: the bottom line

    Mistral Small offers significantly lower pricing, while Llama 3.1 Nemotron 70B Instruct leads on benchmark performance. Your choice depends on whether cost efficiency or raw capability matters more for your use case.

    Llama 3.1 Nemotron 70B Instruct vs Mistral Small FAQ

    Which is cheaper, Llama 3.1 Nemotron 70B Instruct or Mistral Small?

    As of August 30, 2026, Mistral Small is 67% cheaper on blended LLM API pricing. Mistral Small costs $0.20 per million input tokens and $0.60 per million output tokens ($0.80 blended 1M-in + 1M-out). Llama 3.1 Nemotron 70B Instruct costs $1.20 / $1.20 per million tokens ($2.40 blended). Sources: https://build.nvidia.com/nvidia/llama-3_1-nemotron-70b-instruct and https://docs.mistral.ai/platform/pricing/. The cheapest LLM for your app still depends on how many output tokens you generate.

    How much does Llama 3.1 Nemotron 70B Instruct vs Mistral Small cost per million tokens?

    Llama 3.1 Nemotron 70B Instruct NVIDIA API pricing is $1.20 input and $1.20 output per million tokens via NVIDIA. Mistral Small Mistral API pricing is $0.20 input and $0.60 output per million tokens via Mistral AI. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.

    Which is better for coding, Llama 3.1 Nemotron 70B Instruct or Mistral Small?

    Neither Llama 3.1 Nemotron 70B Instruct nor Mistral Small has a published SWE-bench or LiveCodeBench score on this page yet. Use the comparison table for the evals that do exist.

    What is the context window for Llama 3.1 Nemotron 70B Instruct vs Mistral Small?

    Llama 3.1 Nemotron 70B Instruct supports a 131K token context window, while Mistral Small supports 33K tokens. Llama 3.1 Nemotron 70B Instruct offers a larger context window. Filling a larger window bills more input tokens, so the cheaper-per-million model can still cost more on long documents.

    Which model performs better on benchmarks, Llama 3.1 Nemotron 70B Instruct or Mistral Small?

    Llama 3.1 Nemotron 70B Instruct leads on 1 of 1 shared benchmarks versus Mistral Small's 0 wins. Check the comparison table for GPQA Diamond, SWE-bench, MMLU, HLE, and the other evals we track. Token price and benchmark score together are the usual LLM comparison, not either number alone.

    Is Llama 3.1 Nemotron 70B Instruct or Mistral Small better for production use?

    Both Llama 3.1 Nemotron 70B Instruct and Mistral Small are production API models. For cost-sensitive production traffic, Mistral Small has better economics on the blended 1M-in + 1M-out scale. For maximum capability, weight the benchmark table for your domain. Many production stacks route cheap models for drafts and a frontier model for the hard turn, which is usually cheaper than sending everything to the expensive API.

    Can I switch between Llama 3.1 Nemotron 70B Instruct and Mistral Small in my app?

    Yes. Call Llama 3.1 Nemotron 70B Instruct through NVIDIA and Mistral Small through Mistral AI with separate API keys, or through a gateway that already wraps both. Keep prompts in tokens, not characters, when you estimate the invoice. AnotherWrapper templates can swap providers without rewriting auth and billing.

    How accurate is this Llama 3.1 Nemotron 70B Instruct vs Mistral Small pricing data?

    List rates are the latest published NVIDIA API pricing and Mistral API pricing, quoted per million tokens. Official rate sheets: https://build.nvidia.com/nvidia/llama-3_1-nemotron-70b-instruct and https://docs.mistral.ai/platform/pricing/. Prompt caching, batch APIs, and committed-use discounts can change the invoice. Benchmark scores are from official publications and independent evals, updated as new numbers land.

    What is the output token limit for Llama 3.1 Nemotron 70B Instruct and Mistral Small?

    Llama 3.1 Nemotron 70B Instruct supports up to an unspecified number of output tokens per request, while Mistral Small supports up to 33K output tokens. Output tokens are usually the expensive half of API pricing, so a higher max output cap is a capability, not a discount.

    Which model has better throughput, Llama 3.1 Nemotron 70B Instruct or Mistral Small?

    Mistral Small has a measured throughput of approximately 0.1 tokens/second. Throughput data for Llama 3.1 Nemotron 70B Instruct is not yet available. Throughput (tokens per second) and time-to-first-token are why two models with the same per-million-token price can still feel different in chat and agents.

    How do I switch the models in this Llama 3.1 Nemotron 70B Instruct vs Mistral Small comparison?

    Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open Llama 3.1 Nemotron 70B Instruct or Mistral Small from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.

    Llama 3.1 Nemotron 70B Instruct vs Mistral Small pricing

    This comparison covers API pricing, context window, throughput, and benchmark scores. Llama 3.1 Nemotron 70B Instruct costs $1.20/M input and $1.20/M output. Mistral Small costs $0.20/M input and $0.60/M output via Mistral AI.

    Rank both on the LLM leaderboard, SWE-bench, and Humanity's Last Exam.

    The index

    All Large Language Models

    343 models across 36 providers. Search or jump to a lab — every model page stays linked here.

    Baidu

    2 models

    Inception

    1 models

    inclusionAI

    1 models

    LG AI Research

    1 models

    Liquid AI

    2 models

    Nous Research

    1 models

    OpenBMB

    1 models

    Sakana AI

    1 models

    Sarvam AI

    2 models

    Tencent

    1 models

    Thinking Machines

    1 models

    Unisound

    1 models

    Upstage

    1 models

    Next step

    You found the model. Now ship the product.

    Auth, billing, and the API layer are already decided. Fork 8 finished AI apps, or have us build the first version with you.