API cost decision in 10 seconds

GLM 4.6V vs INTELLECT-3

The standard workload cost is tied; choose by context window, provider fit, latency, or model quality.

Page updated: 2026-05-26T10:03:26Z Data confirmed: 2026-05-26T13:08:02Z Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

The standard workload cost is tied; choose by context window, provider fit, latency, or model quality.

Both models are estimated at $0.75 for the standard 1M input plus 500K output workload.

Cost-first pickTie

Context-first pickBoth models

Sample savings$00%

10x traffic gap$0

Context-window winner: Both models. Cost does not separate this pair on the standard workload, so the next decision point is context window and model behavior.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Cost winner changes by workload shape: input-heavy / RAG favors INTELLECT-3, balanced workload favors GLM 4.6V, and output-heavy chatbot favors GLM 4.6V.

Workload shape	Token mix	Better pick	GLM 4.6V	INTELLECT-3
Input-heavy / RAG	5M input + 500K output	INTELLECT-3	$1.95	$1.55
Balanced workload	1M input + 1M output	GLM 4.6V	$1.2	$1.3
Output-heavy chatbot	1M input + 5M output	GLM 4.6V	$4.8	$5.7

Cheaper input INTELLECT-3 $0.3 vs $0.2 / 1M

INTELLECT-3 is $0.1 cheaper per 1M input tokens (33.3% lower; 1.5x difference).

Cheaper output GLM 4.6V $0.9 vs $1.1 / 1M

GLM 4.6V is $0.2 cheaper per 1M output tokens (18.2% lower; 1.22x difference).

Larger context Tie 131.07K vs 131.07K

Both models report the same context window at 131.07K tokens.

Sample workload Tie $0.75 vs $0.75

Both models have the same estimated cost for the standard 1M input plus 500K output workload: $0.75.

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.

Monthly input tokens Monthly output tokens

GLM 4.6V Calculating… Estimated API cost

INTELLECT-3 Calculating… Estimated API cost

Cheaper for this workload Calculating… Difference: calculating…

This estimate uses normalized public API pricing per 1M tokens. It is a planning aid, not a billing quote. Verify provider pricing, limits, and terms before production use.

Quick Decision

Verdict

INTELLECT-3 has the lower input price; GLM 4.6V has the lower output price; both models report the same context window. For the 1M input plus 500K output sample, the standard workload cost is tied.

For a 1M input token plus 500K output token workload, the estimated API cost is $0.75 for GLM 4.6V and $0.75 for INTELLECT-3.

Best Fit

Choose GLM 4.6V when you care most about lower output-token price.

Choose INTELLECT-3 when you care most about lower input-token price.

Decision Notes

Both models are estimated at $0.75 for the standard 1M input plus 500K output workload.
Both models have the same estimated cost for the standard 1M input plus 500K output workload: $0.75.
INTELLECT-3 is $0.1 cheaper per 1M input tokens (33.3% lower; 1.5x difference).
GLM 4.6V is $0.2 cheaper per 1M output tokens (18.2% lower; 1.22x difference).
Both models report the same context window at 131.07K tokens.

Head-to-Head Specs

Feature	GLM 4.6V (Z.ai)	INTELLECT-3 (Prime Intellect)
Input Price prompt tokens per 1M	$0.3	$0.2
Completion Price per 1M tokens	$0.9	$1.1
Sample Workload Cost 1M input + 500K output	$0.75	$0.75
Context Window	131.07K	131.07K
Release Date	2025-12-08	2025-11-27

Use-Case Decision Matrix

Use case	Better pick	Why
Budget-constrained production	Tie	Both models are estimated at $0.75 for the standard 1M input plus 500K output workload.
High-volume input processing	INTELLECT-3	Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbots	GLM 4.6V	Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document work	Tie	A larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Same-provider lower-cost swaps

GLM 4.5 Air (free) can replace GLM 4.6V when lower sample workload cost matters most: $0.
GLM 4 32B can replace GLM 4.6V when lower sample workload cost matters most: $0.15.
GLM 4.7 Flash can replace GLM 4.6V when lower sample workload cost matters most: $0.26.
GLM 4.5 Air can replace GLM 4.6V when lower sample workload cost matters most: $0.55.

Larger context near this budget

Llama 4 Scout offers 10M context with $0.23 sample workload cost.
Owl Alpha offers 1.05M context with $0 sample workload cost.
DeepSeek V4 Flash offers 1.05M context with $0.2 sample workload cost.
DeepSeek V4 Pro offers 1.05M context with $0.87 sample workload cost.

Popular competitors

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Cheaper alternatives

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Larger context alternatives

Find models with larger context windows for RAG, long documents, and codebase review.

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Provider catalogs

Compare models within provider hubs before choosing a final API vendor.

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Z.ai catalog

Review all tracked Z.ai models before deciding whether this matchup is the right shortlist.

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Prime Intellect catalog

Check other Prime Intellect models with comparable pricing, context, or release timing.

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GLM 4.6V

GLM-4.6V is a large multimodal model designed for high-fidelity visual understanding and long-context reasoning across images, documents, and mixed media. It supports up to 128K tokens, processes complex page layouts...

INTELLECT-3

INTELLECT-3 is a 106B-parameter Mixture-of-Experts model (12B active) post-trained from GLM-4.5-Air-Base using supervised fine-tuning (SFT) followed by large-scale reinforcement learning (RL). It offers state-of-the-art performance for its size across math,...