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GLM 5.2 vs R1 Distill Llama 70B

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for GLM 5.2 and R1 Distill Llama 70B.

Zhipu AI

GLM 5.2

GLM 5.2 is a large-scale reasoning model from Z.ai. It supports text input and output with a 1M-token context window, and is suited for long-horizon agent workflows, project-level software engineering,...

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DeepSeek

R1 Distill Llama 70B

DeepSeek R1 Distill Llama 70B is a distilled large language model based on [Llama-3.3-70B-Instruct](/meta-llama/llama-3.3-70b-instruct), using outputs from [DeepSeek R1](/deepseek/deepseek-r1). The model combines advanced distillation techniques to achieve high performance across...

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Technical Specifications

SpecificationGLM 5.2R1 Distill Llama 70B
ProviderZhipu AIDeepSeek
Context Window1,048,576 tokens128,000 tokens
Agent SuitabilityN/AN/A
Time to First Token (TTFT)N/AN/A
Deployment Modelmanaged apiself hostable
Production Stabilitybetastable
API AvailableYesYes
Released Date2026-06-162025-01-23

API Pricing Comparison

Input Price per Million Tokens

GLM 5.2

$0.93

R1 Distill Llama 70B

$0.80

Output Price per Million Tokens

GLM 5.2

$3.00

R1 Distill Llama 70B

$0.80

Want to test both models live?

Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

MMLUGeneral knowledge & multi-task understanding
8950.0%vs8520.0%
GLM 5.2
R1 Distill Llama 70B
HumanEvalPython coding & logic synthesis
9120.0%vs8830.0%
GLM 5.2
R1 Distill Llama 70B
MATHComplex mathematical problem solving
8050.0%vs7000.0%
GLM 5.2
R1 Distill Llama 70B
GPQAGraduate-level expert reasoning
5350.0%vs4450.0%
GLM 5.2
R1 Distill Llama 70B
HellaSwagCommonsense reasoning and inference
8980.0%vs8600.0%
GLM 5.2
R1 Distill Llama 70B
MT-BenchMulti-turn conversation flow quality
930.0%vs905.0%
GLM 5.2
R1 Distill Llama 70B

GLM 5.2 Quirks & Gotchas

No developer gotchas reported.

R1 Distill Llama 70B Quirks & Gotchas

No developer gotchas reported.