Saba vs Qwen-Plus
Updated October 21, 2026. No benchmark has tested both models yet. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
- Coding
- No data
- Overall
- 6.5
- Output $/M
- $0.60
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.78
Decision reading
Neither model has a coding score yet, so the two cannot be ranked on coding.
Saba has the edge where output tokens cost 1.3x less.
No benchmark has tested both yet. Saba has results on AA Intelligence Index, GPQA Diamond (Artificial Analysis run) and Humanity's Last Exam (Artificial Analysis run); Qwen-Plus on LMArena Text: coding, LMArena Text: software and IT and GPQA Diamond (Epoch AI run). 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
Intelligence
AA Intelligence Index
No call
Only Saba has a AA Intelligence Index result, 6.5.
Directional only
Long documents
Listed context window
Qwen-Plus
Qwen-Plus takes 1M tokens against 33K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Saba
Saba $0.0005, Qwen-Plus $0.0006 per turn.
List prices
At a glance
- Coding index
- Saba not benchmarked, Qwen-Plus 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
- Saba $0.60 against Qwen-Plus $0.78 per million output tokens, 1.3x apart.
- Context window
- Saba takes 33K tokens, Qwen-Plus 1M.
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.
CodingDirectional onlySix of these boards feed the Vibe Coding Index2 boards measured
| Benchmark | Saba | Qwen-Plus | Leader |
|---|---|---|---|
| LMArena Text: coding | Not measured | 1328 | Only Qwen-Plus measured |
| LMArena Text: software and IT | Not measured | 1343 | Only Qwen-Plus measured |
| Neither model has a result on the other 36 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Saba | Qwen-Plus | Leader |
|---|---|---|---|
| AA Intelligence Index | 6.5 | Not measured | Only Saba measured |
| Neither model has a result on the other 1 board here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
| Benchmark | Saba | Qwen-Plus | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 42.4% | Not measured | Only Saba measured |
| Humanity's Last Exam (Artificial Analysis run) | 4.3% | Not measured | Only Saba measured |
| GPQA Diamond (Epoch AI run) | Not measured | 48.1% | Only Qwen-Plus measured |
| LMArena Text: hard prompts | Not measured | 1317 | Only Qwen-Plus measured |
| LMArena Text: expert | Not measured | 1328 | Only Qwen-Plus measured |
| LMArena Text: hard prompts in English | Not measured | 1333 | Only Qwen-Plus measured |
| Neither model has a result on the other 15 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | Saba | Qwen-Plus | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 17.8% | Only Qwen-Plus measured |
| MATH level 5 | Not measured | 65.3% | Only Qwen-Plus measured |
| LMArena Text: math | Not measured | 1326 | Only Qwen-Plus measured |
| LMArena Text: mathematical work | Not measured | 1332 | Only Qwen-Plus measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | Saba | Qwen-Plus | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 61.1% | Not measured | Only Saba measured |
| LMArena Text: science | Not measured | 1352 | Only Qwen-Plus measured |
| LMArena Text: medicine and healthcare | Not measured | 1350 | Only Qwen-Plus measured |
| LMArena Text: legal and government | Not measured | 1349 | Only Qwen-Plus measured |
| LMArena Text: business and finance | Not measured | 1303 | Only Qwen-Plus measured |
| Neither model has a result on the other 12 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index14 boards measured
| Benchmark | Saba | Qwen-Plus | Leader |
|---|---|---|---|
| DTBench | Not measured | 81.1% | Only Qwen-Plus measured |
| LMCA | Not measured | 24.0% | Only Qwen-Plus measured |
| LMArena Text | Not measured | 1326 | Only Qwen-Plus measured |
| LMArena Text: instruction following | Not measured | 1303 | Only Qwen-Plus measured |
| LMArena Text: creative writing | Not measured | 1292 | Only Qwen-Plus measured |
| LMArena Text: English | Not measured | 1339 | Only Qwen-Plus measured |
| LMArena Text: non-English | Not measured | 1310 | Only Qwen-Plus measured |
| LMArena Text: Chinese | Not measured | 1347 | Only Qwen-Plus measured |
| LMArena Text: Japanese | Not measured | 1251 | Only Qwen-Plus measured |
| LMArena Text: Russian | Not measured | 1323 | Only Qwen-Plus measured |
| LMArena Text: multi-turn | Not measured | 1336 | Only Qwen-Plus measured |
| LMArena Text: longer queries | Not measured | 1324 | Only Qwen-Plus measured |
| LMArena Text: writing and language | Not measured | 1296 | Only Qwen-Plus measured |
| LMArena Text: entertainment and media | Not measured | 1270 | Only Qwen-Plus measured |
| Neither model has a result on the other 32 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
Saba costs less
Repository review
50K input + 3K output tokens
Saba costs less
Agent loop
200K input + 10K output tokens
Saba 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 | Mistral Saba | Qwen-Plus |
|---|---|---|
| Maker | Mistral AI | Qwen |
| Weights | No public weights listed | No public weights listed |
| Released | February 17, 2025 | February 1, 2025 |
| Context window | 33K | 1M |
| Input $/Mtok | $0.20 | $0.26 |
| Output $/Mtok | $0.60 | $0.78 |
| 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 Saba better than Qwen-Plus for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Saba has the edge where output tokens cost 1.3x less.
Which is cheaper, Saba or Qwen-Plus?
Saba costs $0.20 per million input tokens and $0.60 per million output tokens; Qwen-Plus costs $0.26 and $0.78. Cost per solved task is known for neither of them.
Which has the bigger context window, Saba or Qwen-Plus?
Qwen-Plus, with 1M tokens against 33K.
Has any benchmark tested both Saba and Qwen-Plus?
No benchmark has tested both yet. Saba has results on AA Intelligence Index, GPQA Diamond (Artificial Analysis run) and Humanity's Last Exam (Artificial Analysis run); Qwen-Plus on LMArena Text: coding, LMArena Text: software and IT and GPQA Diamond (Epoch AI run). Compare them on price and context instead. Data as of October 21, 2026.