Which is cheaper, Granite 3.3 8B Instruct or Phi 4?
As of August 25, 2026, Phi 4 is 79% cheaper on blended LLM API pricing. Phi 4 costs $0.07 per million input tokens and $0.14 per million output tokens ($0.21 blended 1M-in + 1M-out). Granite 3.3 8B Instruct costs $0.50 / $0.50 per million tokens ($1.00 blended). Sources: https://anotherwrapper.com/tools/llm-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 Granite 3.3 8B Instruct vs Phi 4 cost per million tokens?
Granite 3.3 8B Instruct IBM API pricing is $0.50 input and $0.50 output per million tokens via IBM. Phi 4 Microsoft API pricing is $0.07 input and $0.14 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, Granite 3.3 8B Instruct or Phi 4?
Granite 3.3 8B Instruct leads on HumanEval: Granite 3.3 8B Instruct at 89.7% vs Phi 4 at 82.6%. SWE-bench measures real GitHub fixes; LiveCodeBench measures contest programming.
What is the context window for Granite 3.3 8B Instruct vs Phi 4?
Granite 3.3 8B Instruct supports a 128K token context window, while Phi 4 supports 16K tokens. Granite 3.3 8B 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, Granite 3.3 8B Instruct or Phi 4?
Phi 4 leads on 3 of 5 shared benchmarks versus Granite 3.3 8B Instruct's 2 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 Granite 3.3 8B Instruct or Phi 4 better for production use?
Both Granite 3.3 8B Instruct and Phi 4 are production API models. For cost-sensitive production traffic, Phi 4 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 Granite 3.3 8B Instruct and Phi 4 in my app?
Yes. Call Granite 3.3 8B Instruct through IBM and Phi 4 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 Granite 3.3 8B Instruct vs Phi 4 pricing data?
List rates are the latest published IBM API pricing and Microsoft API pricing, quoted per million tokens. Official rate sheets: https://anotherwrapper.com/tools/llm-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 Granite 3.3 8B Instruct and Phi 4?
Granite 3.3 8B Instruct supports up to 8K output tokens per request, while Phi 4 supports up to 16K 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, Granite 3.3 8B Instruct or Phi 4?
Granite 3.3 8B Instruct runs at approximately 50 tokens/second while Phi 4 runs at 33 tokens/second. Granite 3.3 8B Instruct is faster in raw throughput. 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 Granite 3.3 8B Instruct vs Phi 4 comparison?
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open Granite 3.3 8B Instruct or Phi 4 from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.
