As of August 20, 2026, GLM-5V-Turbo is 35% cheaper per million tokens than Grok 4.6. GLM-5V-Turbo is $1.20 / $4.00 per million input/output tokens versus Grok 4.6 at $2.00 / $6.00. Sources: https://docs.z.ai/guides/overview/pricing and https://docs.x.ai/docs/models
Sources: Z AI pricing (https://docs.z.ai/guides/overview/pricing); xAI API pricing (https://docs.x.ai/docs/models)
GLM-5V-Turbo
Z AI
Input
$1.20
Output
$4.00
Grok 4.6
xAI
Input
$2.00
Output
$6.00
Token pricing, specs, and benchmarks side by side
GLM-5V-TurboGrok 4.6Verdict
GLM-5V-Turbo offers significantly lower pricing, while Grok 4.6 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, GLM-5V-Turbo is 35% cheaper on blended LLM API pricing. GLM-5V-Turbo costs $1.20 per million input tokens and $4.00 per million output tokens ($5.20 blended 1M-in + 1M-out). Grok 4.6 costs $2.00 / $6.00 per million tokens ($8.00 blended). Sources: https://docs.z.ai/guides/overview/pricing and https://docs.x.ai/docs/models. The cheapest LLM for your app still depends on how many output tokens you generate.
GLM-5V-Turbo Z AI API pricing is $1.20 input and $4.00 output per million tokens via Z AI. Grok 4.6 xAI API pricing is $2.00 input and $6.00 output per million tokens via xAI. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Grok 4.6 has a published SWE-bench Verified score of 95.6%. GLM-5V-Turbo does not have that eval on this page yet.
GLM-5V-Turbo supports a 203K token context window, while Grok 4.6 supports 500K tokens. Grok 4.6 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.
Grok 4.6 leads on 1 of 1 shared benchmarks versus GLM-5V-Turbo'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 GLM-5V-Turbo and Grok 4.6 are production API models. For cost-sensitive production traffic, GLM-5V-Turbo 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 GLM-5V-Turbo through Z AI and Grok 4.6 through xAI 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 Z AI API pricing and xAI API pricing, quoted per million tokens. Official rate sheets: https://docs.z.ai/guides/overview/pricing and https://docs.x.ai/docs/models. 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.
GLM-5V-Turbo supports up to 128K output tokens per request, while Grok 4.6 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.
Grok 4.6 has a measured throughput of approximately 4.687848222704461 tokens/second. Throughput data for GLM-5V-Turbo 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.
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open GLM-5V-Turbo or Grok 4.6 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. GLM-5V-Turbo costs $1.20/M input and $4.00/M output. Grok 4.6 costs $2.00/M input and $6.00/M output.
Rank both on the LLM leaderboard, SWE-bench, and Humanity's Last Exam.
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