| Signal | GPT-5.1-Codex-Max | Delta | Llama 3.3 70B Instruct (free) |
|---|---|---|---|
Capabilities | 100 | +67 | |
Pricing | 10 | -20 | |
Context window size | 89 | +8 | |
Recency | 100 | +52 | |
Output Capacity | 85 | -- | |
| Overall Result | 3 wins | of 5 | 1 wins |
30
days ranked higher
0
days
0
days ranked higher
OpenAI
Meta
Llama 3.3 70B Instruct (free) saves you $625.00/month
That's $7500.00/year compared to GPT-5.1-Codex-Max at your current usage level of 100K calls/month.
| Metric | GPT-5.1-Codex-Max | Llama 3.3 70B Instruct (free) | Winner |
|---|---|---|---|
| Overall Score | 96 | 54 | GPT-5.1-Codex-Max |
| Rank | #12 | #238 | GPT-5.1-Codex-Max |
| Quality Rank | #12 | #238 | GPT-5.1-Codex-Max |
| Adoption Rank | #12 | #238 | GPT-5.1-Codex-Max |
| Parameters | -- | 70B | -- |
| Context Window | 400K | 128K | GPT-5.1-Codex-Max |
| Pricing | $1.25/$10.00/M | Free | -- |
| Signal Scores | |||
| Capabilities | 100 | 33 | GPT-5.1-Codex-Max |
| Pricing | 10 | 30 | Llama 3.3 70B Instruct (free) |
| Context window size | 89 | 81 | GPT-5.1-Codex-Max |
| Recency | 100 | 48 | GPT-5.1-Codex-Max |
| Output Capacity | 85 | 85 | GPT-5.1-Codex-Max |
Our composite score (0–100) combines six weighted signals: benchmark performance (25%), pricing efficiency (25%), context window size (15%), model recency (15%), output capacity (10%), and capability versatility (10%). Here's what the scores mean for these two models:
Scores 96/100 (rank #12), placing it in the top 96% of all 290 models tracked.
Scores 54/100 (rank #238), placing it in the top 18% of all 290 models tracked.
GPT-5.1-Codex-Max has a 42-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
Both models are priced similarly, so the decision comes down to quality and features rather than cost.
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 3.3 70B Instruct (free) also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (400K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.00/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (96/100) 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
GPT-5.1-Codex-Max clearly outperforms Llama 3.3 70B Instruct (free) with a significant 41.9-point lead. For most general use cases, GPT-5.1-Codex-Max is the stronger choice. However, Llama 3.3 70B Instruct (free) may still excel in niche scenarios.
Best for Quality
GPT-5.1-Codex-Max
Marginally better benchmark scores; both are excellent
Best for Cost
Llama 3.3 70B Instruct (free)
100% lower pricing; better value at scale
Best for Reliability
GPT-5.1-Codex-Max
Higher uptime and faster response speeds
Best for Prototyping
GPT-5.1-Codex-Max
Stronger community support and better developer experience
Best for Production
GPT-5.1-Codex-Max
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-5.1-Codex-Max | Llama 3.3 70B Instruct (free) |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoningdiffers | ||
| Web Searchdiffers | ||
| Image Output |
OpenAI
Meta
Llama 3.3 70B Instruct (free) saves you $14.25/month
That's 100% cheaper than GPT-5.1-Codex-Max 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 | GPT-5.1-Codex-Max | Llama 3.3 70B Instruct (free) |
|---|---|---|
| Context Window | 400K | 128K |
| Max Output Tokens | 128,000 | 128,000 |
| Open Source | No | Yes |
| Created | Dec 4, 2025 | Dec 6, 2024 |
GPT-5.1-Codex-Max scores 96/100 (rank #12) compared to Llama 3.3 70B Instruct (free)'s 54/100 (rank #238), giving it a 42-point advantage. GPT-5.1-Codex-Max is the stronger overall choice, though Llama 3.3 70B Instruct (free) may excel in specific areas like cost efficiency.
GPT-5.1-Codex-Max is ranked #12 and Llama 3.3 70B Instruct (free) is ranked #238 out of 290+ AI models. Rankings use a composite score combining benchmark performance (25%), pricing (25%), context window (15%), recency (15%), output capacity (10%), and versatility (10%). Scores update hourly.
Llama 3.3 70B Instruct (free) is cheaper at $0.00/M output tokens vs GPT-5.1-Codex-Max's $10.00/M output tokens — 10000.0x more expensive. Input token pricing: GPT-5.1-Codex-Max at $1.25/M vs Llama 3.3 70B Instruct (free) at $0.00/M.
GPT-5.1-Codex-Max has a larger context window of 400,000 tokens compared to Llama 3.3 70B Instruct (free)'s 128,000 tokens. A larger context window means the model can process longer documents and conversations.