| Signal | MiniMax M3 | Delta | GLM 4.6V |
|---|---|---|---|
Capabilities | 83 | -- | |
Benchmarks | 73 | +9 | |
Pricing | 99 | 0 | |
Context window size | 86 | +13 | |
Recency | 100 | +4 | |
Output Capacity | 95 | +20 | |
| Overall Result | 4 wins | of 6 | 1 wins |
Score History
74.1
current score
MiniMax M3
right now
65.1
current score
MiniMax
Zhipu AI
GLM 4.6V saves you $15.00/month
That's $180.00/year compared to MiniMax M3 at your current usage level of 100K calls/month.
| Metric | MiniMax M3 | GLM 4.6V | Winner |
|---|---|---|---|
| Overall Score | 74 | 65 | MiniMax M3 |
| Rank | #73 | #124 | MiniMax M3 |
| Quality Rank | #73 | #124 | MiniMax M3 |
| Adoption Rank | #73 | #124 | MiniMax M3 |
| Parameters | -- | -- | -- |
| Context Window | 1049K | 131K | MiniMax M3 |
| Pricing | $0.30/$1.20/M | $0.30/$0.90/M | -- |
| Signal Scores | |||
| Capabilities | 83 | 83 | MiniMax M3 |
| Benchmarks | 73 | 64 | MiniMax M3 |
| Pricing | 99 | 99 | GLM 4.6V |
| Context window size | 86 | 73 | MiniMax M3 |
| Recency | 100 | 96 | MiniMax M3 |
| Output Capacity | 95 | 75 | MiniMax M3 |
Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.
Scores 74/100 (rank #73), placing it in the top 75% of all 290 models tracked.
Scores 65/100 (rank #124), placing it in the top 58% of all 290 models tracked.
MiniMax M3 has a 9-point advantage, which typically translates to noticeably better performance on complex reasoning, code generation, and multi-step tasks.
GLM 4.6V offers 20% better value per quality point. At 1M tokens/day, you'd spend $18.00/month with GLM 4.6V vs $22.50/month with MiniMax M3 - a $4.50 monthly difference.
Both models have comparable response speeds. For most applications, the latency difference is negligible.
When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.
Code generation & review
Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Suitable for user-facing chat with competitive response times. GLM 4.6V also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (1049K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.90/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (74/100) correlates with better nuance, coherence, and style in long-form content
Image understanding & OCR
Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly
MiniMax M3 has a moderate advantage with a 9-point lead in composite score. It wins on more signal dimensions, but GLM 4.6V has specific strengths that could make it the better choice for certain workflows.
Best for Quality
MiniMax M3
Marginally better benchmark scores; both are excellent
Best for Cost
GLM 4.6V
20% lower pricing; better value at scale
Best for Reliability
MiniMax M3
Higher uptime and faster response speeds
Best for Prototyping
MiniMax M3
Stronger community support and better developer experience
Best for Production
MiniMax M3
Wider enterprise adoption and proven at scale
by MiniMax
| Capability | MiniMax M3 | GLM 4.6V |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
MiniMax
Zhipu AI
GLM 4.6V saves you $0.3600/month
That's 18% cheaper than MiniMax M3 at 1,000 tokens/request and 100 requests/day.
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | MiniMax M3 | GLM 4.6V |
|---|---|---|
| Context Window | 1.0M | 131K |
| Max Output Tokens | 512,000 | 32,768 |
| Open Source | Yes | Yes |
| Created | May 31, 2026 | Dec 8, 2025 |