text model comparison
GPT-6.1 Terra vs Grok 4.20
GPT-6.1 Terra and Grok 4.20 are both current text models, from OpenAI and xAI. GPT-6.1 Terra is 20% cheaper per 1M input tokens than Grok 4.20, $1 vs $1.25. GPT-6.1 Terra has the larger context window, 1,050,000 vs 1,000,000 tokens.
- Lower price per 1M input tokens
- GPT-6.1 Terra$1 against $1.25
- Longer context window
- GPT-6.1 Terra1.05M tokens against 1M tokens
- Newer release
- GPT-6.1 TerraOct 2026 against Mar 2026
Data verified October 28, 2026 · Dataset 2026-10-28
Side by side
GPT-6.1 Terra and Grok 4.20, line by line
Prices in effect today, compared at the same tier wherever both list one. The better value in each row is highlighted.
| Fact | GPT-6.1 Terra | Grok 4.20 |
|---|---|---|
| Price | ||
| Price per 1M input tokens | $1 (better) | $1.25 |
| Price per 1M output tokens | $5 | $2.50 (better) |
| Independent benchmarks | ||
| Arena Text | Not measured | 1472 Elo (#26 of 49) |
| GPQA Diamond | Not measured | 89.3% (#31 of 40) |
| FrontierMath Tiers 1-3 (v2) | Not measured | 44.9% (#34 of 40) |
| SimpleQA Verified | Not measured | 30.2% (#32 of 36) |
| Specs | ||
| Provider | OpenAI | xAI |
| Release date | October 26, 2026 | March 10, 2026 |
| Access | API only | API only |
| Context window | 1,050,000 tokens | 1,000,000 tokens |
| Max output | 128,000 tokens | Not reported |
| Input | text, image | text, image |
| Output | text | text |
No independent benchmark has scored both models yet. Each rank counts the current models scored on that benchmark.
Charts
Against every current text model
Where GPT-6.1 Terra and Grok 4.20 land among the current models of their task, on every independent benchmark, on price and on context.
Where each stands
Only Grok 4.20 has a current Arena Text score: #26 of 49. Each bar is the share of current models it beats.
Independent benchmarks
Arena Text
GPT-6.1 Terra: Not scored
Grok 4.20:#26of 49
1,472 Elo · ahead of 48%
GPQA Diamond
GPT-6.1 Terra: Not scored
Grok 4.20:#31of 40
89.3% · ahead of 23%
FrontierMath Tiers 1-3 (v2)
GPT-6.1 Terra: Not scored
Grok 4.20:#34of 40
44.9% · ahead of 15%
SimpleQA Verified
GPT-6.1 Terra: Not scored
Grok 4.20:#32of 36
30.2% · ahead of 11%
Price and context
Price per 1M input tokens
GPT-6.1 Terra:#19of 51
$1 · cheaper than 62%
Grok 4.20:#21of 51
$1.25 · cheaper than 56%
Price per 1M output tokens
GPT-6.1 Terra:#26of 51
$5 · cheaper than 50%
Grok 4.20:#15of 51
$2.50 · cheaper than 68%
Context window
GPT-6.1 Terra:#1of 66
1.05M tokens · longer than 86%
Grok 4.20:#28of 66
1M tokens · longer than 22%
Quality against price
Grok 4.20 scores 1,472 at $1.56 (blended price per 1M tokens). The line joins the current models no other beats on both price and Arena Text score; hover any point to name it.
Quality against price: the data
| Model | Provider | Blended price per 1M tokens | Arena Text (Elo) |
|---|---|---|---|
| Gemini 4 Argon | $4 | 1,525 | |
| Claude Opus 5.5 | Anthropic | $8 | 1,507 |
| Claude Fable 5 | Anthropic | $20 | 1,504 |
| Claude Fable 5.1 | Anthropic | $20 | 1,501 |
| Gemini 3.8 Flash | $1.50 | 1,497 | |
| Muse Spark 1.3 | Meta | $2 | 1,494 |
| Claude Opus 5 | Anthropic | $10 | 1,490 |
| Kimi K3 | Moonshot Kimi | $6 | 1,488 |
| Gemini 3.7 Flash | $1.50 | 1,486 | |
| GPT-5.6 Sol | OpenAI | $8 | 1,485 |
| GPT-6.1 Sol | OpenAI | $4 | 1,484 |
| Qwen3.8-Max | Alibaba Qwen | $3 | 1,483 |
| GPT-5.5 | OpenAI | $11 | 1,482 |
| Gemini 3.6 Flash | $3 | 1,482 | |
| Claude Opus 4.8 | Anthropic | $10 | 1,481 |
| MiMo-V2.6-Pro | Xiaomi MiMo | $0.54 | 1,480 |
| GLM-5.3 | Z.ai | $2.15 | 1,478 |
| Claude Sonnet 5.5 | Anthropic | $4 | 1,476 |
| GPT-5.4 | OpenAI | $5.63 | 1,475 |
| GPT-6 Astra | OpenAI | $20 | 1,475 |
| DeepSeek-V4.1-Flash | DeepSeek | $0.52 | 1,475 |
| GLM-5.3-Flash | Z.ai | $0.24 | 1,475 |
| Gemini 3 Flash Preview | $1.13 | 1,473 | |
| Grok 4.20 | xAI | $1.56 | 1,472 |
| GPT-5.6 Terra | OpenAI | $4.50 | 1,466 |
| Grok 4.5 | xAI | $3 | 1,466 |
| DeepSeek-V4-Pro | DeepSeek | $1.98 | 1,465 |
| Claude Sonnet 5 | Anthropic | $4 | 1,461 |
| GPT-6 Sol | OpenAI | $4 | 1,456 |
| Gemini 3.5 Flash-Lite | $0.85 | 1,455 | |
| Grok 4.6 | xAI | $3 | 1,454 |
| GPT-5.6 Luna | OpenAI | $0.45 | 1,452 |
| MiMo-V2.6-Flash | Xiaomi MiMo | $0.18 | 1,451 |
| GPT-6 Luna | OpenAI | $0.20 | 1,443 |
| Grok 4.7 | xAI | $3 | 1,443 |
| Grok 4.3 | xAI | $1.56 | 1,442 |
| Mistral Large 4 | Mistral AI | $2.06 | 1,429 |
| GPT-4.1 | OpenAI | $3.50 | 1,415 |
| Solar Pro 4 | Upstage | $0.52 | 1,386 |
| GPT-4.1 mini | OpenAI | $0.70 | 1,383 |
| GPT-4.1 nano | OpenAI | $0.18 | 1,322 |
Cost
What each costs
Example workloads at each provider's listed rates, then every other rate either one lists. The cheaper figure in each row is highlighted.
The same work, priced
For 10M input and 2M output tokens, GPT-6.1 Terra costs 1.1 times as much as Grok 4.20, at each provider's listed rates.
10M input and 2M output tokens
GPT-6.1 Terra costs 1.1× as much
- GPT-6.1 Terra
- $20
- Grok 4.20
- $17.50
The same, with 9M of the input tokens cached
GPT-6.1 Terra costs 1.4× as much
- GPT-6.1 Terra
- $11.45
- Grok 4.20
- $8.05
| Workload or rate | GPT-6.1 Terra | Grok 4.20 |
|---|---|---|
| Example workloads | ||
| 10M input and 2M output tokens | $20 | $17.50 (better) |
| The same, with 9M of the input tokens cached | $11.45 | $8.05 (better) |
| Other listed rates | ||
| 1M input tokens, cached | $0.05 (better) | $0.20 |
| 1M input tokens, prompts over 272K tokens | $2 | Not listed |
| 1M output tokens, prompts over 272K tokens | $7.50 | Not listed |
Verdict
When to choose each
GPT-6.1 Terra
Where it leads
- Lower price per 1M input tokens, $1 vs $1.25
- Larger context window 1,050,000 vs 1,000,000 tokens
- Cheaper cached input, $0.05 vs $0.20 per 1M tokens
Best for
- Computer-use and tool-calling agents at half GPT-6.1 Sol's price
- High-volume reasoning work that stays under the 272K long-context threshold
Watch out for
- Prompts over 272,000 input tokens bill the whole request at $2 input and $7.50 output per 1M tokens
- Reads text and images only: audio and video input are not supported
- Released on 26 October 2026, so no independent benchmark score is recorded here yet
Grok 4.20
Where it leads
- Lower price per 1M output tokens, $2.50 vs $5
- Lower cost for 10M input and 2M output tokens, $17.50 vs $20
Best for
- Comparing single-agent and multi-agent reasoning on long-context workloads
Watch out for
- The published base rates double when requests reach the provider's 200,000-token long-context threshold
From benchmark to production
Building on GPT-6.1 Terra or Grok 4.20?
Public scores rarely hold on your own data. We test both models on your real tasks, then build the agent or pipeline around the one that wins.
FAQ
GPT-6.1 Terra vs Grok 4.20 FAQ
Which is cheaper, GPT-6.1 Terra or Grok 4.20?
GPT-6.1 Terra is 20% cheaper per 1M input tokens than Grok 4.20, $1 vs $1.25. For 10M input and 2M output tokens, GPT-6.1 Terra costs $20 and Grok 4.20 $17.50 at standard rates.
Which is cheaper with prompt caching, GPT-6.1 Terra or Grok 4.20?
GPT-6.1 Terra charges $0.05 per 1M cached input tokens, 95% below its standard input rate, and Grok 4.20 $0.20, 84% below. With 9M of 10M input tokens cached and 2M output tokens, GPT-6.1 Terra costs $11.45 and Grok 4.20 $8.05.
Which has the larger context window, GPT-6.1 Terra or Grok 4.20?
GPT-6.1 Terra has the larger context window, 1,050,000 vs 1,000,000 tokens.
Further reading
More on GPT-6.1 Terra and Grok 4.20
Articles on GPT-6.1 Terra and Grok 4.20
- GPT-6.1 Terra: Price, Benchmarks and When to Use ItOctober 27, 2026
Related comparisons
- GPT-5.6 Terra vs GPT-6.1 Terra
- Grok 4.20 vs Grok 4.7
- GPT-6.1 Sol vs GPT-6.1 Terra
- Gemini 3.8 Flash vs Grok 4.20
- GPT-6.1 Terra vs Grok 4.3
- DeepSeek-V4-Pro vs Grok 4.20
- GPT-6.1 Terra vs Muse Spark 1.3
- Gemini 3.7 Flash vs Grok 4.20
- GPT-6.1 Terra vs Step 5 Preview
- Grok 4.20 vs Grok 4.6
- Grok 4.20 vs Grok 4.5
- Gemini 3.1 Pro Preview vs Grok 4.20
Production evaluation
Choosing between GPT-6.1 Terra and Grok 4.20?
Public benchmarks narrow the shortlist. We run both on your own tasks, data and cost limits, then build the routing and review controls to run the winner in production.
- A head-to-head evaluation on your real workload
- Routing between models by cost and difficulty