Gemini 4 Argon vs Grok 4.3
Compare Gemini 4 Argon vs Grok 4.3 API pricing, token costs, context windows, and latency. See which model is cheaper and better for your stack.
Gemini 4 Argon charges $4.00/1M input and $20.00/1M output tokens, compared to Grok 4.3 at $1.25/1M input and $2.50/1M output. Grok 4.3 is 3.2x cheaper on input tokens. In reasoning benchmarks, Gemini 4 Argon holds the higher AA Intelligence Index rating. For latency-critical streaming, Gemini 4 Argon delivers 56 t/s (38.0s TTFT) while Grok 4.3 provides 79 t/s (23.0s TTFT).
Full Metric & Specification Comparison
| Metric | Gemini 4 Argon | Grok 4.3 | Advantage |
|---|---|---|---|
| Provider | xAI | - | |
| Input Token Cost (1M) | $4.000 | $1.250 | Grok 4.3 |
| Output Token Cost (1M) | $20.000 | $2.500 | Grok 4.3 |
| Context Window | 1,000k tokens | 1,000k tokens | Tie |
| AA Intelligence Index | 50/100 | Unrated | Unrated |
| Streaming Latency | Moderate | Moderate | - |
Key Architectural Takeaways
- Input Token Cost: Gemini 4 Argon is $4.00/1M vs Grok 4.3 at $1.25/1M
- Output Token Cost: Gemini 4 Argon is $20.00/1M vs Grok 4.3 at $2.50/1M
- Context Window: Gemini 4 Argon supports 1,000k tokens vs Grok 4.3 with 1,000k tokens
- Benchmark Intelligence Rating: not rated for one or both models
- Inference Latency: Gemini 4 Argon is rated Moderate vs Grok 4.3 rated Moderate
Calculate Your Team's Exact Bill Difference
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Deploying Grok 4.3 over Gemini 4 Argon saves $172.50/mo ($2070/yr) at this volume.
Frequently Asked Questions
Is Gemini 4 Argon cheaper than Grok 4.3?
Grok 4.3 is significantly more economical, charging $1.25/1M input compared to $4.00/1M for Gemini 4 Argon.
Which model should I choose for production?
If your primary constraint is API cost and high query throughput, choose Grok 4.3. If you require peak reasoning accuracy and complex tool use, Gemini 4 Argon is recommended.
How does context window compare between Gemini 4 Argon and Grok 4.3?
Gemini 4 Argon offers the larger context window (1,000k tokens), allowing you to pass significantly larger codebases or documents without chunking.
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