As of August 20, 2026, Grok 4.3 is 24% cheaper per million tokens than Sakana Namazu. Grok 4.3 is $1.25 / $2.50 per million input/output tokens versus Sakana Namazu at $0.95 / $4.00. Sources: https://docs.x.ai/docs/models and https://sakana.ai
Sources: xAI API pricing (https://docs.x.ai/docs/models); Sakana AI pricing (https://sakana.ai)
Grok 4.3
xAI
Input
$1.25
Output
$2.50
Sakana Namazu
Sakana AI
Input
$0.95
Output
$4.00
Token pricing, specs, and benchmarks side by side
Grok 4.3Sakana NamazuVerdict
Grok 4.3 offers significantly lower pricing, while Sakana Namazu leads on benchmark performance. Your choice depends on whether cost efficiency or raw capability matters more for your use case.
As of August 20, 2026, Grok 4.3 is 24% cheaper on blended LLM API pricing. Grok 4.3 costs $1.25 per million input tokens and $2.50 per million output tokens ($3.75 blended 1M-in + 1M-out). Sakana Namazu costs $0.95 / $4.00 per million tokens ($4.95 blended). Sources: https://docs.x.ai/docs/models and https://sakana.ai. The cheapest LLM for your app still depends on how many output tokens you generate.
Grok 4.3 xAI API pricing is $1.25 input and $2.50 output per million tokens via xAI. Sakana Namazu Sakana AI API pricing is $0.95 input and $4.00 output per million tokens via Sakana AI. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Grok 4.3 has a published SWE-bench Verified score of 71.4%. Sakana Namazu does not have that eval on this page yet.
Grok 4.3 supports a 1M token context window, while Sakana Namazu supports 256K tokens. Grok 4.3 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.
Sakana Namazu leads on 1 of 1 shared benchmarks versus Grok 4.3'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.
Both Grok 4.3 and Sakana Namazu are production API models. For cost-sensitive production traffic, Grok 4.3 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.
Yes. Call Grok 4.3 through xAI and Sakana Namazu through Sakana 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.
List rates are the latest published xAI API pricing and Sakana AI API pricing, quoted per million tokens. Official rate sheets: https://docs.x.ai/docs/models and https://sakana.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.
Grok 4.3 supports up to an unspecified number of output tokens per request, while Sakana Namazu supports up to 256K output tokens. Output tokens are usually the expensive half of API pricing, so a higher max output cap is a capability, not a discount.
Neither Grok 4.3 nor Sakana Namazu has published throughput data on this page yet. 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.
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open Grok 4.3 or Sakana Namazu from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.
This comparison covers API pricing, context window, throughput, and benchmark scores. Grok 4.3 costs $1.25/M input and $2.50/M output. Sakana Namazu costs $0.95/M input and $4.00/M output.
Rank both on the LLM leaderboard, SWE-bench, and Humanity's Last Exam.
The index
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