DeepSeek R1 Distill Llama 70B vs GLM-5.3-Flash
Comparing DeepSeek R1 Distill Llama 70B and GLM-5.3-Flash across benchmarks, pricing, and capabilities.
DeepSeek · Zhipu AI · Updated for 2026
Which is better?
DeepSeek R1 Distill Llama 70B and GLM-5.3-Flash trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, DeepSeek R1 Distill Llama 70B is roughly 1.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GLM-5.3-Flash also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Based on current benchmark, pricing, and model metadata for 2026.
Choose DeepSeek R1 Distill Llama 70B
- cost matters — it's about 1.4x cheaper per token
Choose GLM-5.3-Flash
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Aug 2026
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek R1 Distill Llama 70B and GLM-5.3-Flashdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek R1 Distill Llama 70B ($0.10/1M tokens) is 1.5x cheaper than GLM-5.3-Flash ($0.15/1M tokens).
For output processing, DeepSeek R1 Distill Llama 70B ($0.40/1M tokens) is 1.3x cheaper than GLM-5.3-Flash ($0.50/1M tokens).
In conclusion, GLM-5.3-Flash is more expensive than DeepSeek R1 Distill Llama 70B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-5.3-Flash has 249.4B more parameters than DeepSeek R1 Distill Llama 70B, making it 353.3% larger.
Context Window
Maximum input and output token capacity
GLM-5.3-Flash accepts 1,048,576 input tokens compared to DeepSeek R1 Distill Llama 70B's 128,000 tokens. GLM-5.3-Flash can generate longer responses up to 131,072 tokens, while DeepSeek R1 Distill Llama 70B is limited to 128,000 tokens.
Input Capabilities
Supported data types and modalities
GLM-5.3-Flash supports multimodal inputs, whereas DeepSeek R1 Distill Llama 70B does not.
GLM-5.3-Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek R1 Distill Llama 70B
GLM-5.3-Flash
License
Usage and distribution terms
Both models are licensed under MIT.
Both models share the same licensing terms, providing consistent usage rights.
MIT
Open weights
MIT
Open weights
Release Timeline
When each model was launched
DeepSeek R1 Distill Llama 70B was released on 2025-01-20, while GLM-5.3-Flash was released on 2026-08-26.
GLM-5.3-Flash is 19 months newer than DeepSeek R1 Distill Llama 70B.
Jan 20, 2025
1.6 years ago
Aug 26, 2026
0 days ago
1.6yr newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek R1 Distill Llama 70B is available from DeepInfra. GLM-5.3-Flash is available from DeepInfra, Novita, ZAI.
DeepSeek R1 Distill Llama 70B
GLM-5.3-Flash
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek R1 Distill Llama 70B and GLM-5.3-Flash side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek R1 Distill Llama 70B vs GLM-5.3-Flash.