GLM 4.7 Flash is $0.04 cheaper per 1M input tokens (40% lower; 1.67x difference).
API cost decision in 10 seconds
GLM 4.7 Flash vs Llama 3.3 70B Instruct
The standard workload cost is tied; choose by context window, provider fit, latency, or model quality.
Page updated:
Data confirmed:
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 $0.26 for the standard 1M input plus 500K output workload.
Cost-first pickTie
Context-first pickGLM 4.7 Flash
Sample savings$00%
10x traffic gap$0
Context-window winner: GLM 4.7 Flash. 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
Cost winner changes by workload shape: input-heavy / RAG favors GLM 4.7 Flash, balanced workload favors Llama 3.3 70B Instruct, and output-heavy chatbot favors Llama 3.3 70B Instruct.
| Workload shape | Token mix | Better pick | GLM 4.7 Flash | Llama 3.3 70B Instruct |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | GLM 4.7 Flash | $0.5 | $0.66 |
| Balanced workload | 1M input + 1M output | Llama 3.3 70B Instruct | $0.46 | $0.42 |
| Output-heavy chatbot | 1M input + 5M output | Llama 3.3 70B Instruct | $2.06 | $1.7 |
Llama 3.3 70B Instruct is $0.08 cheaper per 1M output tokens (20% lower; 1.25x difference).
GLM 4.7 Flash has 71.68K more context (1.55x larger).
Both models have the same estimated cost for the standard 1M input plus 500K output workload: $0.26.
Estimate your workload cost
Your Workload Cost
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
GLM 4.7 Flash has the lower input price; Llama 3.3 70B Instruct has the lower output price; GLM 4.7 Flash offers the larger 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 $0.26 for GLM 4.7 Flash and $0.26 for Llama 3.3 70B Instruct.
Choose GLM 4.7 Flash when you care most about lower input-token price, and larger context window.
Choose Llama 3.3 70B Instruct when you care most about lower output-token price.
- Both models are estimated at $0.26 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: $0.26.
- GLM 4.7 Flash is $0.04 cheaper per 1M input tokens (40% lower; 1.67x difference).
- Llama 3.3 70B Instruct is $0.08 cheaper per 1M output tokens (20% lower; 1.25x difference).
- GLM 4.7 Flash has 71.68K more context (1.55x larger).
| Feature | GLM 4.7 Flash (Z.ai) | Llama 3.3 70B Instruct (Meta) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.06 | $0.1 |
| Completion Price per 1M tokens | $0.4 | $0.32 |
| Sample Workload Cost 1M input + 500K output | $0.26 | $0.26 |
| Context Window | 202.75K | 131.07K |
| Release Date | ||
| Popularity | #58 | #88 |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | Tie | Both models are estimated at $0.26 for the standard 1M input plus 500K output workload. |
| High-volume input processing | GLM 4.7 Flash | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | Llama 3.3 70B Instruct | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | GLM 4.7 Flash | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
- GLM 4.5 Air (free) can replace GLM 4.7 Flash when lower sample workload cost matters most: $0.
- GLM 4 32B can replace GLM 4.7 Flash when lower sample workload cost matters most: $0.15.
- Llama 3.3 70B Instruct (free) can replace Llama 3.3 70B Instruct when lower sample workload cost matters most: $0.
- Llama 3.2 3B Instruct (free) can replace Llama 3.3 70B Instruct when lower sample workload cost matters most: $0.
- 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.
- Gemini 2.5 Flash Lite offers 1.05M context with $0.3 sample workload cost.
- DeepSeek V4 Flash · DeepSeek · #1
- Hy3 preview · Tencent · #2
- Claude Opus 4.7 · Anthropic · #3
- Claude Sonnet 4.6 · Anthropic · #4
Cheaper alternatives
Review low-cost models sorted by a standard 1M input plus 500K output workload.
Open cheapest modelsLarger context alternatives
Find models with larger context windows for RAG, long documents, and codebase review.
Open largest context modelsProvider catalogs
Compare models within provider hubs before choosing a final API vendor.
Open provider hubsZ.ai catalog
Review all tracked Z.ai models before deciding whether this matchup is the right shortlist.
Open Z.ai modelsMeta catalog
Check other Meta models with comparable pricing, context, or release timing.
Open Meta modelsAs a 30B-class SOTA model, GLM-4.7-Flash offers a new option that balances performance and efficiency. It is further optimized for agentic coding use cases, strengthening coding capabilities, long-horizon task planning,...
The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model...