MiniMax-01 vs Sonar Deep Research
MiniMax-01 costs 7.3x less per output token than Sonar Deep Research ($1.10 vs $8.00 per million). Updated October 21, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $1.10
- Coding
- No data
- Overall
- No data
- Output $/M
- $8.00
MiniMax-01 or Sonar Deep Research: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick MiniMax-01 for output tokens 7.3x cheaper ($1.10 vs $8.00 per million) and a larger context window (1M against 128K tokens).
No benchmark has tested both yet. MiniMax-01 has results on Kagi LLM Benchmark; Sonar Deep Research has none yet. Compare them on price and context instead.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Long documents
Listed context window
MiniMax-01
MiniMax-01 takes 1M tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiniMax-01
MiniMax-01 $0.0008, Sonar Deep Research $0.0060 per turn.
List prices
At a glance
- Coding index
- MiniMax-01 not benchmarked, Sonar Deep Research not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- MiniMax-01 $1.10 against Sonar Deep Research $8.00 per million output tokens, 7.3x apart.
- Context window
- MiniMax-01 takes 1M tokens, Sonar Deep Research 128K.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | MiniMax-01 | Sonar Deep Research | Leader |
|---|---|---|---|
| Kagi LLM Benchmark | 42.5% | Not measured | Only MiniMax-01 measured |
| Neither model has a result on the other 21 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
MiniMax-01 costs less
Repository review
50K input + 3K output tokens
MiniMax-01 costs less
Agent loop
200K input + 10K output tokens
MiniMax-01 costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | MiniMax-01 | Perplexity Sonar Deep Research |
|---|---|---|
| Maker | MiniMax | Perplexity |
| Weights | Open weights | No public weights listed |
| Released | January 15, 2025 | March 7, 2025 |
| Context window | 1M | 128K |
| Input $/Mtok | $0.20 | $2.00 |
| Output $/Mtok | $1.10 | $8.00 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is MiniMax-01 better than Sonar Deep Research for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick MiniMax-01 for output tokens 7.3x cheaper ($1.10 vs $8.00 per million) and a larger context window (1M against 128K tokens).
Which is cheaper, MiniMax-01 or Sonar Deep Research?
MiniMax-01 costs $0.20 per million input tokens and $1.10 per million output tokens; Sonar Deep Research costs $2.00 and $8.00. Cost per solved task is known for neither of them.
Which has the bigger context window, MiniMax-01 or Sonar Deep Research?
MiniMax-01, with 1M tokens against 128K.
Has any benchmark tested both MiniMax-01 and Sonar Deep Research?
No benchmark has tested both yet. MiniMax-01 has results on Kagi LLM Benchmark; Sonar Deep Research has none yet. Compare them on price and context instead. Data as of October 21, 2026.