| Signal | Llama 3.1 70B Instruct | Delta | GLM 5 Turbo |
|---|---|---|---|
Capabilities | 50 | -17 | |
Benchmarks | 75 | +0 | |
Pricing | 100 | +4 | |
Context window size | 81 | -3 | |
Recency | 20 | -80 | |
Output Capacity | 20 | -65 | |
| Overall Result | 2 wins | of 6 | 4 wins |
Score History
67.3
current score
GLM 5 Turbo
right now
67.6
current score
Meta
Zhipu AI
Llama 3.1 70B Instruct saves you $260.00/month
That's $3120.00/year compared to GLM 5 Turbo at your current usage level of 100K calls/month.
| Metric | Llama 3.1 70B Instruct | GLM 5 Turbo | Winner |
|---|---|---|---|
| Overall Score | 67 | 68 | GLM 5 Turbo |
| Rank | #71 | #69 | GLM 5 Turbo |
| Quality Rank | #71 | #69 | GLM 5 Turbo |
| Adoption Rank | #71 | #69 | GLM 5 Turbo |
| Parameters | 70B | -- | -- |
| Context Window | 131K | 203K | GLM 5 Turbo |
| Pricing | $0.40/$0.40/M | $1.20/$4.00/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 67 | GLM 5 Turbo |
| Benchmarks | 75 | 74 | Llama 3.1 70B Instruct |
| Pricing | 100 | 96 | Llama 3.1 70B Instruct |
| Context window size | 81 | 84 | GLM 5 Turbo |
| Recency | 20 | 100 | GLM 5 Turbo |
| Output Capacity | 20 | 85 | GLM 5 Turbo |
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 67/100 (rank #71), placing it in the top 76% of all 290 models tracked.
Scores 68/100 (rank #69), placing it in the top 77% of all 290 models tracked.
With only a 0-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.
Llama 3.1 70B Instruct offers 85% better value per quality point. At 1M tokens/day, you'd spend $12.00/month with Llama 3.1 70B Instruct vs $78.00/month with GLM 5 Turbo - a $66.00 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
Higher benchmark score (0/100) indicates stronger performance on coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Faster response time (speed score 0/100) is critical for user-facing chat. Llama 3.1 70B Instruct also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (203K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.40/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (68/100) correlates with better nuance, coherence, and style in long-form content
Llama 3.1 70B Instruct and GLM 5 Turbo are extremely close in overall performance (only 0.29999999999999716 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Llama 3.1 70B Instruct
Marginally better benchmark scores; both are excellent
Best for Cost
Llama 3.1 70B Instruct
85% lower pricing; better value at scale
Best for Reliability
Llama 3.1 70B Instruct
Higher uptime and faster response speeds
Best for Prototyping
Llama 3.1 70B Instruct
Stronger community support and better developer experience
Best for Production
Llama 3.1 70B Instruct
Wider enterprise adoption and proven at scale
by Meta
| Capability | Llama 3.1 70B Instruct | GLM 5 Turbo |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
Meta
Zhipu AI
Llama 3.1 70B Instruct saves you $5.76/month
That's 83% cheaper than GLM 5 Turbo 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 | Llama 3.1 70B Instruct | GLM 5 Turbo |
|---|---|---|
| Context Window | 131K | 203K |
| Max Output Tokens | -- | 131,072 |
| Open Source | Yes | No |
| Created | Jul 23, 2024 | Mar 15, 2026 |
GLM 5 Turbo scores 68/100 (rank #69) compared to Llama 3.1 70B Instruct's 67/100 (rank #71), giving it a 0-point advantage. GLM 5 Turbo is the stronger overall choice, though Llama 3.1 70B Instruct may excel in specific areas like cost efficiency.
Llama 3.1 70B Instruct is ranked #71 and GLM 5 Turbo is ranked #69 out of 290+ AI models. Rankings use a composite score combining benchmark performance (90%) from MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations, with capabilities and context window as tiebreakers (10%). Scores update hourly.
Llama 3.1 70B Instruct is cheaper at $0.40/M output tokens vs GLM 5 Turbo's $4.00/M output tokens - 10.0x more expensive. Input token pricing: Llama 3.1 70B Instruct at $0.40/M vs GLM 5 Turbo at $1.20/M.
GLM 5 Turbo has a larger context window of 202,752 tokens compared to Llama 3.1 70B Instruct's 131,072 tokens. A larger context window means the model can process longer documents and conversations.