Gemini 3.5 Flash-Lite vs Phi-3.5-mini-instruct

    Comparison

    As of August 20, 2026, Phi-3.5-mini-instruct is 93% cheaper per million tokens than Gemini 3.5 Flash-Lite. Gemini 3.5 Flash-Lite is $0.30 / $2.50 per million input/output tokens versus Phi-3.5-mini-instruct at $0.10 / $0.10. Sources: https://ai.google.dev/gemini-api/docs/pricing and https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/

    Sources: Gemini API pricing (https://ai.google.dev/gemini-api/docs/pricing); Microsoft pricing (https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/)

    Gemini 3.5 Flash-Lite

    Google

    $2.80blended / 1M

    Input

    $0.30

    Output

    $2.50

    1M ctx|Proprietary
    93%
    cheaper
    Better value

    Phi-3.5-mini-instruct

    Microsoft

    $0.20blended / 1M

    Input

    $0.10

    Output

    $0.10

    128K ctx|Open Source
    Save $2.60 per million tokens by choosing Phi-3.5-mini-instruct over Gemini 3.5 Flash-Lite.

    Gemini 3.5 Flash-Lite vs Phi-3.5-mini-instruct comparison

    Token pricing, specs, and benchmarks side by side

    Metric
    Gemini 3.5 Flash-Lite
    Phi-3.5-mini-instruct
    Provider
    Provider
    Google
    Microsoft
    License
    Proprietary
    Open Source
    Release Date
    2026-07-21
    2024-08-23
    Pricing (per 1M tokens)
    Input Price+200%
    $0.30
    $0.10
    Output Price+2400%
    $2.50
    $0.10
    Blended (1M + 1M)
    $2.80
    $0.20
    Model Details
    Context Window
    1M
    128K
    Max Output Tokens
    65.5K
    128K
    Knowledge Cutoff
    2026-03-31
    N/A
    Throughput
    N/A
    23 tok/s
    Benchmarks
    30.4%
    75.8%
    40.9%
    10.3%
    74%
    55.4%
    76.5%
    60%
    69%
    83.6%
    69.4%
    62.8%
    48.5%
    84.6%
    78%
    60.7%
    0%
    72.3%
    43.2%
    10%
    25.9%
    86.2%
    26.2%
    69.6%
    43.5%
    70.9%
    61.7%
    62.2%
    46.5%
    63.1%
    47.9%
    39.2%
    85.8%
    47.4%
    21.3%
    79.2%
    81%
    41.9%
    21.3%
    77%
    84.1%
    47.3%
    74.7%
    24.3%
    72.6%
    68.5%
    Benchmark Wins
    Gemini 3.5 Flash-Lite 1|0 Phi-3.5-mini-instruct

    Verdict

    Gemini 3.5 Flash-Lite vs Phi-3.5-mini-instruct: the bottom line

    Phi-3.5-mini-instruct offers significantly lower pricing, while Gemini 3.5 Flash-Lite leads on benchmark performance. Your choice depends on whether cost efficiency or raw capability matters more for your use case.

    Gemini 3.5 Flash-Lite vs Phi-3.5-mini-instruct FAQ

    Which is cheaper, Gemini 3.5 Flash-Lite or Phi-3.5-mini-instruct?

    As of August 20, 2026, Phi-3.5-mini-instruct is 93% cheaper on blended LLM API pricing. Phi-3.5-mini-instruct costs $0.10 per million input tokens and $0.10 per million output tokens ($0.20 blended 1M-in + 1M-out). Gemini 3.5 Flash-Lite costs $0.30 / $2.50 per million tokens ($2.80 blended). Sources: https://ai.google.dev/gemini-api/docs/pricing and https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/. The cheapest LLM for your app still depends on how many output tokens you generate.

    How much does Gemini 3.5 Flash-Lite vs Phi-3.5-mini-instruct cost per million tokens?

    Gemini 3.5 Flash-Lite Gemini API pricing is $0.30 input and $2.50 output per million tokens via Google. Phi-3.5-mini-instruct Microsoft API pricing is $0.10 input and $0.10 output per million tokens via Microsoft. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.

    Which is better for coding, Gemini 3.5 Flash-Lite or Phi-3.5-mini-instruct?

    Gemini 3.5 Flash-Lite has a published SWE-bench Verified score of 75%. Phi-3.5-mini-instruct does not have that eval on this page yet.

    What is the context window for Gemini 3.5 Flash-Lite vs Phi-3.5-mini-instruct?

    Gemini 3.5 Flash-Lite supports a 1M token context window, while Phi-3.5-mini-instruct supports 128K tokens. Gemini 3.5 Flash-Lite 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, Gemini 3.5 Flash-Lite or Phi-3.5-mini-instruct?

    Gemini 3.5 Flash-Lite leads on 1 of 1 shared benchmarks versus Phi-3.5-mini-instruct'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 Gemini 3.5 Flash-Lite or Phi-3.5-mini-instruct better for production use?

    Both Gemini 3.5 Flash-Lite and Phi-3.5-mini-instruct are production API models. For cost-sensitive production traffic, Phi-3.5-mini-instruct 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 Gemini 3.5 Flash-Lite and Phi-3.5-mini-instruct in my app?

    Yes. Call Gemini 3.5 Flash-Lite through Google and Phi-3.5-mini-instruct through Microsoft 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 Gemini 3.5 Flash-Lite vs Phi-3.5-mini-instruct pricing data?

    List rates are the latest published Gemini API pricing and Microsoft API pricing, quoted per million tokens. Official rate sheets: https://ai.google.dev/gemini-api/docs/pricing and https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/. 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 Gemini 3.5 Flash-Lite and Phi-3.5-mini-instruct?

    Gemini 3.5 Flash-Lite supports up to 66K output tokens per request, while Phi-3.5-mini-instruct supports up to 128K 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, Gemini 3.5 Flash-Lite or Phi-3.5-mini-instruct?

    Phi-3.5-mini-instruct has a measured throughput of approximately 23 tokens/second. Throughput data for Gemini 3.5 Flash-Lite 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 Gemini 3.5 Flash-Lite vs Phi-3.5-mini-instruct comparison?

    Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open Gemini 3.5 Flash-Lite or Phi-3.5-mini-instruct from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.

    Gemini 3.5 Flash-Lite vs Phi-3.5-mini-instruct pricing

    This comparison covers API pricing, context window, throughput, and benchmark scores. Gemini 3.5 Flash-Lite costs $0.30/M input and $2.50/M output. Phi-3.5-mini-instruct costs $0.10/M input and $0.10/M output.

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

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