MODEL COMPARISON
GPT-6.1 Sol vs Gemini 4 Argon
Gemini 4 Argon scores higher on the Artificial Analysis Intelligence Index (52.6 vs 51.8 for GPT-6.1 Sol); GPT-6.1 Sol costs less per task ($0.7242 vs $1.99 for Gemini 4 Argon). Both run through one SandBase API key.
- Cost per taskGPT-6.1 Sol64% cheaper
Which one to pick
Each line is backed by a number in the table below.
- The hardest reasoningGemini 4 Argon
Gemini 4 Argon leads the Intelligence Index, 52.6 against 51.8.
- High request volumeGPT-6.1 Sol
GPT-6.1 Sol finishes the same index for $0.7242 instead of $1.99, so the gap compounds with every run.
Side by side
Prices are per 1M tokens on SandBase, after any public discount. Better value per row is marked.
| Metric | GPT-6.1 Sol | Gemini 4 Argon |
|---|---|---|
| Input / 1M tokens | $2Better | $4 |
| Output / 1M tokens | $10Better | $20 |
| Context window | 1.1MBetter | 1M |
| Intelligence IndexAA | 51.8 | 52.6Better |
| Cost per taskAA | $0.7242Better | $1.99 |
| Output speedAA | 49 tok/s | — |
Rows marked AA — Data: Artificial Analysis, snapshot 2026-10-14. GPT-6.1 Sol on AA ↗ Gemini 4 Argon on AA ↗ Full rankings: SandBase Lab leaderboards.
Switching between them
Same key, same endpoint, same request shape.
curl https://api.sandbase.ai/v1/chat/completions \
-H "Authorization: Bearer $SANDBASE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "openai/gpt-6.1-sol",
"messages": [{"role": "user", "content": "Hello"}]
}'To run the same prompt on Gemini 4 Argon, change "model" to google/gemini-4-argon. Nothing else changes, so you can A/B both on your own prompts before committing.
Both models
Pricing, playground and reference for each.
OpenAI
GPT-6.1 Sol
openai/gpt-6.1-solGPT-6.1 Sol is OpenAI's upgrade to GPT-6 Sol, introduced at DevDay 2026 and positioned between GPT-6 Astra and GPT-6 Luna, with text and image input. OpenAI says it delivers near-Astra performance for complex coding, computer use and professional work, and recommends comparing it with Astra on your own tasks. Pick it for demanding agentic work at scale when Astra's full depth is not required; it always reasons at least at a low level and has no reasoning-off option.
Gemini 4 Argon
google/gemini-4-argonGemini 4 Argon is Google's flagship reasoning model and the first model of the Gemini 4 generation, generally available since October 13, 2026. Google trained it to keep context and precision across long, multi-step work such as complex software engineering, legal and financial research, and cybersecurity defense. It accepts text, image, video, audio and PDF input with a 1M-token context window, always reasons before answering with low, medium or high effort, and supports function calling and structured output.
FAQ
Which is cheaper, GPT-6.1 Sol or Gemini 4 Argon?
On SandBase GPT-6.1 Sol is $2 per 1M input tokens and $10 per 1M output tokens; Gemini 4 Argon is $4 and $20. GPT-6.1 Sol has the lower output price.
Is GPT-6.1 Sol better than Gemini 4 Argon?
On the Artificial Analysis Intelligence Index GPT-6.1 Sol scores 51.8 and Gemini 4 Argon scores 52.6, so Gemini 4 Argon is ahead on general capability. Cost and speed can point the other way, so check the table above for the metric that matters to your workload.
What does each model cost per task?
Artificial Analysis measures $0.7242 per task for GPT-6.1 Sol and $1.99 for Gemini 4 Argon, running the same Intelligence Index workload. That figure folds in how many tokens each model spends on reasoning, so it tracks real spend better than the per-token price alone.
How big is the context window of each model?
GPT-6.1 Sol accepts 1.1M tokens and Gemini 4 Argon accepts 1M tokens per request.
Can I use both GPT-6.1 Sol and Gemini 4 Argon with one API key?
Yes. Both run through SandBase, so a single API key and balance covers them and the rest of the catalog. You do not need separate OpenAI and Google developer accounts.
How do I switch between GPT-6.1 Sol and Gemini 4 Argon?
Change the model field in your request from "openai/gpt-6.1-sol" to "google/gemini-4-argon". The endpoint, key and request shape stay the same, which makes it cheap to A/B the two on your own prompts.
Where do these benchmark numbers come from?
The Intelligence, Coding and Agentic indexes, cost per task and output speed come from Artificial Analysis, from the snapshot dated 2026-10-14. Prices are SandBase list prices after any public discount. Numbers move as new snapshots land.
Keep comparing
See all comparisons, browse the language model catalog, or check the full Artificial Analysis leaderboards in SandBase Lab.