GLM-4.7-Flash vs Laguna S 2.1

    Comparison

    As of August 20, 2026, GLM-4.7-Flash is 100% cheaper per million tokens than Laguna S 2.1. GLM-4.7-Flash is $0.00 / $0.00 per million input/output tokens versus Laguna S 2.1 at $0.10 / $0.20. Sources: https://docs.z.ai/guides/overview/pricing and https://poolside.ai

    Sources: Z AI pricing (https://docs.z.ai/guides/overview/pricing); Poolside pricing (https://poolside.ai)

    Better value

    GLM-4.7-Flash

    Z AI

    $0.00blended / 1M

    Input

    $0.00

    Output

    $0.00

    202.8K ctx|Open Source
    100%
    cheaper

    Laguna S 2.1

    Poolside

    $0.30blended / 1M

    Input

    $0.10

    Output

    $0.20

    1M ctx|Open Source
    Save $0.30 per million tokens by choosing GLM-4.7-Flash over Laguna S 2.1.

    GLM-4.7-Flash vs Laguna S 2.1 comparison

    Token pricing, specs, and benchmarks side by side

    Metric
    GLM-4.7-Flash
    Laguna S 2.1
    Provider
    Provider
    Z AI
    Poolside
    License
    Open Source
    Open Source
    Release Date
    2026-01-19
    2026-07-21
    Pricing (per 1M tokens)
    Input Price-100%
    $0.00
    $0.10
    Output Price-100%
    $0.00
    $0.20
    Blended (1M + 1M)
    $0.00
    $0.30
    Model Details
    Context Window
    202.8K
    1M
    Max Output Tokens
    16.4K
    N/A
    Knowledge Cutoff
    N/A
    N/A
    Throughput
    50 tok/s
    N/A
    Benchmarks
    14.4%
    75.2%
    40.4%
    42.8%
    49.7%
    91.6%
    79.5%

    Verdict

    GLM-4.7-Flash vs Laguna S 2.1: the bottom line

    Both models are closely matched on benchmarks. GLM-4.7-Flash has the pricing advantage, making it the better value unless Laguna S 2.1's specific capabilities are critical to your workflow.

    GLM-4.7-Flash vs Laguna S 2.1 FAQ

    Which is cheaper, GLM-4.7-Flash or Laguna S 2.1?

    As of August 20, 2026, GLM-4.7-Flash is 100% cheaper on blended LLM API pricing. GLM-4.7-Flash costs $0.00 per million input tokens and $0.00 per million output tokens ($0.00 blended 1M-in + 1M-out). Laguna S 2.1 costs $0.10 / $0.20 per million tokens ($0.30 blended). Sources: https://docs.z.ai/guides/overview/pricing and https://poolside.ai. The cheapest LLM for your app still depends on how many output tokens you generate.

    How much does GLM-4.7-Flash vs Laguna S 2.1 cost per million tokens?

    GLM-4.7-Flash Z AI API pricing is $0.00 input and $0.00 output per million tokens via Z AI. Laguna S 2.1 Poolside API pricing is $0.10 input and $0.20 output per million tokens via Poolside. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.

    Which is better for coding, GLM-4.7-Flash or Laguna S 2.1?

    GLM-4.7-Flash has a published SWE-bench Verified score of 59.2%. Laguna S 2.1 does not have that eval on this page yet.

    What is the context window for GLM-4.7-Flash vs Laguna S 2.1?

    GLM-4.7-Flash supports a 203K token context window, while Laguna S 2.1 supports 1M tokens. Laguna S 2.1 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, GLM-4.7-Flash or Laguna S 2.1?

    Shared benchmark scores for GLM-4.7-Flash and Laguna S 2.1 are still limited. Check the comparison table for the evals each model has published. 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 GLM-4.7-Flash or Laguna S 2.1 better for production use?

    Both GLM-4.7-Flash and Laguna S 2.1 are production API models. For cost-sensitive production traffic, GLM-4.7-Flash 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 GLM-4.7-Flash and Laguna S 2.1 in my app?

    Yes. Call GLM-4.7-Flash through Z AI and Laguna S 2.1 through Poolside 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 GLM-4.7-Flash vs Laguna S 2.1 pricing data?

    List rates are the latest published Z AI API pricing and Poolside API pricing, quoted per million tokens. Official rate sheets: https://docs.z.ai/guides/overview/pricing and https://poolside.ai. 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 GLM-4.7-Flash and Laguna S 2.1?

    GLM-4.7-Flash supports up to 16K output tokens per request, while Laguna S 2.1 supports up to an unspecified number of 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, GLM-4.7-Flash or Laguna S 2.1?

    GLM-4.7-Flash has a measured throughput of approximately 50 tokens/second. Throughput data for Laguna S 2.1 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 GLM-4.7-Flash vs Laguna S 2.1 comparison?

    Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open GLM-4.7-Flash or Laguna S 2.1 from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.

    GLM-4.7-Flash vs Laguna S 2.1 pricing

    This comparison covers API pricing, context window, throughput, and benchmark scores. GLM-4.7-Flash costs $0.00/M input and $0.00/M output. Laguna S 2.1 costs $0.10/M input and $0.20/M output.

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

    The index

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