Mixtral 8x22B Instruct vs GLM 4.5V
| Signal | Mixtral 8x22B Instruct | Delta | GLM 4.5V |
|---|---|---|---|
Capabilities | 50 | -33 | |
Benchmarks | 71 | +10 | |
Pricing | 94 | -4 | |
Context window size | 76 | -- | |
Recency | 0 | -67 | |
Output Capacity | 20 | -50 | |
| Overall Result | 1 wins | of 6 | 4 wins |
Score History
63.4
current score
Mixtral 8x22B Instruct
right now
62.5
current score
Mixtral 8x22B Instruct
Mistral AI
GLM 4.5V
Zhipu AI
GLM 4.5V saves you $350.00/month
That's $4200.00/year compared to Mixtral 8x22B Instruct at your current usage level of 100K calls/month.
| Metric | Mixtral 8x22B Instruct | GLM 4.5V | Winner |
|---|---|---|---|
| Overall Score | 63 | 63 | Mixtral 8x22B Instruct |
| Rank | #201 | #202 | Mixtral 8x22B Instruct |
| Quality Rank | #201 | #202 | Mixtral 8x22B Instruct |
| Adoption Rank | #201 | #202 | Mixtral 8x22B Instruct |
| Parameters | 22B | -- | -- |
| Context Window | 66K | 66K | -- |
| Pricing | $2.00/$6.00/M | $0.60/$1.80/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 83 | GLM 4.5V |
| Benchmarks | 71 | 61 | Mixtral 8x22B Instruct |
| Pricing | 94 | 98 | GLM 4.5V |
| Context window size | 76 | 76 | Mixtral 8x22B Instruct |
| Recency | 0 | 67 | GLM 4.5V |
| Output Capacity | 20 | 70 | GLM 4.5V |
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 63/100 (rank #201), placing it in the top 31% of all 290 models tracked.
Scores 63/100 (rank #202), placing it in the top 31% of all 290 models tracked.
With only a 1-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.
Choose Mixtral 8x22B Instruct when you need:
- Self-hosted deployments where you need full control over the model
Choose GLM 4.5V when you need:
- High-volume production workloads where API costs must be minimized
- Multimodal workflows that require image understanding
- Step-by-step reasoning and chain-of-thought problem solving
- Self-hosted deployments where you need full control over the model
GLM 4.5V offers 70% better value per quality point. At 1M tokens/day, you'd spend $36.00/month with GLM 4.5V vs $120.00/month with Mixtral 8x22B Instruct - a $84.00 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 4.5V also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (66K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($1.80/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (63/100) 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
Mixtral 8x22B Instruct and GLM 4.5V are extremely close in overall performance (only 0.8999999999999986 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
By Use Case
Best for Quality
Mixtral 8x22B Instruct
Marginally better benchmark scores; both are excellent
Best for Cost
GLM 4.5V
70% lower pricing; better value at scale
Best for Reliability
Mixtral 8x22B Instruct
Higher uptime and faster response speeds
Best for Prototyping
Mixtral 8x22B Instruct
Stronger community support and better developer experience
Best for Production
Mixtral 8x22B Instruct
Wider enterprise adoption and proven at scale
by Mistral AI
- Choose for Quality - Marginally better benchmark scores; both are excellent
- Choose for Reliability - Higher uptime and faster response speeds
- Choose for Prototyping - Stronger community support and better developer experience
- Choose for Production - Wider enterprise adoption and proven at scale
| Capability | Mixtral 8x22B Instruct | GLM 4.5V |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
Mixtral 8x22B Instruct
Mistral AI
GLM 4.5V
Zhipu AI
GLM 4.5V saves you $7.56/month
That's 70% cheaper than Mixtral 8x22B Instruct 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 | Mixtral 8x22B Instruct | GLM 4.5V |
|---|---|---|
| Context Window | 66K | 66K |
| Max Output Tokens | -- | 16,384 |
| Open Source | Yes | Yes |
| Created | Apr 17, 2024 | Aug 11, 2025 |