| Signal | Gemma 3 4B | Delta | GPT-5.3-Codex |
|---|---|---|---|
Capabilities | 50 | -50 | |
Pricing | 0 | -14 | |
Context window size | 81 | -8 | |
Recency | 65 | -35 | |
Output Capacity | 20 | -65 | |
| Overall Result | 0 wins | of 5 | 5 wins |
0
days ranked higher
0
days
30
days ranked higher
OpenAI
Gemma 3 4B saves you $867.00/month
That's $10404.00/year compared to GPT-5.3-Codex at your current usage level of 100K calls/month.
| Metric | Gemma 3 4B | GPT-5.3-Codex | Winner |
|---|---|---|---|
| Overall Score | 56 | 85 | GPT-5.3-Codex |
| Rank | #240 | #29 | GPT-5.3-Codex |
| Quality Rank | #240 | #29 | GPT-5.3-Codex |
| Adoption Rank | #240 | #29 | GPT-5.3-Codex |
| Parameters | 4B | -- | -- |
| Context Window | 131K | 400K | GPT-5.3-Codex |
| Pricing | $0.04/$0.08/M | $1.75/$14.00/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 100 | GPT-5.3-Codex |
| Pricing | 0 | 14 | GPT-5.3-Codex |
| Context window size | 81 | 89 | GPT-5.3-Codex |
| Recency | 65 | 100 | GPT-5.3-Codex |
| Output Capacity | 20 | 85 | GPT-5.3-Codex |
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 56/100 (rank #240), placing it in the top 18% of all 290 models tracked.
Scores 85/100 (rank #29), placing it in the top 90% of all 290 models tracked.
GPT-5.3-Codex has a 29-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
Gemma 3 4B offers 99% better value per quality point. At 1M tokens/day, you'd spend $1.80/month with Gemma 3 4B vs $236.25/month with GPT-5.3-Codex - a $234.45 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. Gemma 3 4B 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 ($0.08/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (85/100) 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-5.3-Codex clearly outperforms Gemma 3 4B with a significant 28.799999999999997-point lead. For most general use cases, GPT-5.3-Codex is the stronger choice. However, Gemma 3 4B may still excel in niche scenarios.
Best for Quality
Gemma 3 4B
Marginally better benchmark scores; both are excellent
Best for Cost
Gemma 3 4B
99% lower pricing; better value at scale
Best for Reliability
Gemma 3 4B
Higher uptime and faster response speeds
Best for Prototyping
Gemma 3 4B
Stronger community support and better developer experience
Best for Production
Gemma 3 4B
Wider enterprise adoption and proven at scale
by Google
| Capability | Gemma 3 4B | GPT-5.3-Codex |
|---|---|---|
| Vision (Image Input) | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Searchdiffers | ||
| Image Output |
OpenAI
Gemma 3 4B saves you $19.78/month
That's 99% cheaper than GPT-5.3-Codex 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 | Gemma 3 4B | GPT-5.3-Codex |
|---|---|---|
| Context Window | 131K | 400K |
| Max Output Tokens | -- | 128,000 |
| Open Source | Yes | No |
| Created | Mar 13, 2025 | Feb 24, 2026 |
GPT-5.3-Codex scores 85/100 (rank #29) compared to Gemma 3 4B's 56/100 (rank #240), giving it a 29-point advantage. GPT-5.3-Codex is the stronger overall choice, though Gemma 3 4B may excel in specific areas like cost efficiency.
Gemma 3 4B is ranked #240 and GPT-5.3-Codex is ranked #29 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.
Gemma 3 4B is cheaper at $0.08/M output tokens vs GPT-5.3-Codex's $14.00/M output tokens - 175.0x more expensive. Input token pricing: Gemma 3 4B at $0.04/M vs GPT-5.3-Codex at $1.75/M.
GPT-5.3-Codex has a larger context window of 400,000 tokens compared to Gemma 3 4B's 131,072 tokens. A larger context window means the model can process longer documents and conversations.