Grok 4.7 vs Saba
Updated October 21, 2026. 2 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
vs boards won of 2 shared
Decision reading
Only Grok 4.7 has a coding score, 66.7 on the Vibe Coding Index; Saba has none, so the two cannot be ranked on coding.
Saba has the edge where output tokens cost 10.0x less.
Model AGrok 4.7xAI66.7/1005 independent benchmarksNo cost per solved taskModel BSabaMistral AINot benchmarkedNo coding benchmarkNo cost per solved task
- Shared results
- 2
- Grok 4.7 only
- 97
- Saba only
- 2
- Like-for-like categories
- 2 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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
Only Grok 4.7 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Grok 4.7
Grok 4.7 leads, 46.4 against 6.5.
Same board, both measured
Web design
Design Arena: websites
No call
Only Grok 4.7 has a Design Arena: websites result, 1254.
Directional only
General
Vals Index
No call
Only Grok 4.7 has a Vals Index result, 58.6%.
Directional only
Long documents
Listed context window
Grok 4.7
Grok 4.7 takes 500K tokens against 33K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Saba
Grok 4.7 $0.0050, Saba $0.0005 per turn.
List prices
At a glance
- Coding index
- Grok 4.7 66.7 from 5 benchmarks, Saba not benchmarked.
- Widest category
- Intelligence, 39.9 points apart on average over 1 shared benchmark.
- Widest single gap
- AA Intelligence Index: Grok 4.7 46.4 against Saba 6.5, 39.9 points apart on a 0 to 100 scale.
- Output price
- Grok 4.7 $6.00 against Saba $0.60 per million output tokens, 10.0x apart.
- Context window
- Grok 4.7 takes 500K tokens, Saba 33K.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | Grok 4.7 | Bars | Saba | Ties |
|---|---|---|---|---|
| Intelligence | 1 | 0 | ||
| Reasoning | 1 | 0 | ||
| All shared boards | 2 | 0 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index18 boards, none shared
| Benchmark | Grok 4.7 | Saba | Leader |
|---|---|---|---|
| LiveBench coding | 84.5% | Not measured | Only Grok 4.7 measured |
| LMArena WebDev | 1637 | Not measured | Only Grok 4.7 measured |
| Terminal-Bench 4 (Vals AI) | 28.8% | Not measured | Only Grok 4.7 measured |
| Vibe Code Bench (Vals AI) | 86.2% | Not measured | Only Grok 4.7 measured |
| Code migration (Vals AI) | 44.8% | Not measured | Only Grok 4.7 measured |
| ProgramBench (Vals AI) | 0.5% | Not measured | Only Grok 4.7 measured |
| IOI (Vals AI) | 57.7% | Not measured | Only Grok 4.7 measured |
| Terminal-Bench 2.1 (Vals AI) | 73.4% | Not measured | Only Grok 4.7 measured |
| SWE-bench Multimodal (Vals AI) | 42.9% | Not measured | Only Grok 4.7 measured |
| CyberBench (Vals AI) | 69.5% | Not measured | Only Grok 4.7 measured |
| SciCode | 57.8% | Not measured | Only Grok 4.7 measured |
| FrontierCode | 47.6% | Not measured | Only Grok 4.7 measured |
| FrontierSWE | 29.5% | Not measured | Only Grok 4.7 measured |
| LMArena Text: coding | 1432 | Not measured | Only Grok 4.7 measured |
| LMArena Text: software and IT | 1421 | Not measured | Only Grok 4.7 measured |
| LMArena WebDev: React | 1663 | Not measured | Only Grok 4.7 measured |
| LMArena WebDev: HTML | 1627 | Not measured | Only Grok 4.7 measured |
| LMArena WebDev: from an image | 1586 | Not measured | Only Grok 4.7 measured |
| Neither model has a result on the other 20 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Grok 4.7 | Saba | Leader |
|---|---|---|---|
| AA Intelligence Index | 46.4 | 6.5 | Grok 4.7 |
| Epoch Capabilities Index | 154.4 | Not measured | Only Grok 4.7 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index15 boards, none shared
| Benchmark | Grok 4.7 | Saba | Leader |
|---|---|---|---|
| LiveBench research | 86.4% | Not measured | Only Grok 4.7 measured |
| LiveBench browser | 60.0% | Not measured | Only Grok 4.7 measured |
| LiveBench long agentic | 50.1% | Not measured | Only Grok 4.7 measured |
| SREBench (Vals AI) | 3.8% | Not measured | Only Grok 4.7 measured |
| Finance Agent (Vals AI) | 52.3% | Not measured | Only Grok 4.7 measured |
| Tax Agent Bench (Vals AI) | 34.2% | Not measured | Only Grok 4.7 measured |
| Legal Research Bench (Vals AI) | 47.1% | Not measured | Only Grok 4.7 measured |
| Harvey's Legal Agent Benchmark (Vals AI) | 18.3% | Not measured | Only Grok 4.7 measured |
| Excel Modeling Benchmark (Vals AI) | 67.0% | Not measured | Only Grok 4.7 measured |
| BioMysteryBench (Vals AI) | 69.3% | Not measured | Only Grok 4.7 measured |
| Terminal-Bench-Science (Vals AI) | 10.0% | Not measured | Only Grok 4.7 measured |
| Vals Science Index | 34.8% | Not measured | Only Grok 4.7 measured |
| Robo-bench (Vals AI) | 0.2% | Not measured | Only Grok 4.7 measured |
| APEX-Agents | 54.6% | Not measured | Only Grok 4.7 measured |
| Vending-Bench 2 | $10,537 | Not measured | Only Grok 4.7 measured |
| Neither model has a result on the other 24 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Grok 4.7 | Saba | Leader |
|---|---|---|---|
| LiveBench reasoning | 82.7% | Not measured | Only Grok 4.7 measured |
| MysteryMechanism (Vals AI) | 25.2% | Not measured | Only Grok 4.7 measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 42.4% | Only Saba measured |
| Humanity's Last Exam (Artificial Analysis run) | 43.1% | 4.3% | Grok 4.7 |
| GPQA Diamond (Epoch AI run) | 92.7% | Not measured | Only Grok 4.7 measured |
| ARC-AGI | 90.2% | Not measured | Only Grok 4.7 measured |
| ARC-AGI-2 | 61.4% | Not measured | Only Grok 4.7 measured |
| Chess puzzles | 41.0% | Not measured | Only Grok 4.7 measured |
| Mystery game puzzles | 29.0% | Not measured | Only Grok 4.7 measured |
| LMArena Text: hard prompts | 1415 | Not measured | Only Grok 4.7 measured |
| LMArena Text: expert | 1439 | Not measured | Only Grok 4.7 measured |
| LMArena Text: hard prompts in English | 1427 | Not measured | Only Grok 4.7 measured |
| LMArena Vision: diagrams | 1254 | Not measured | Only Grok 4.7 measured |
| LMArena Vision: homework | 1309 | Not measured | Only Grok 4.7 measured |
| Neither model has a result on the other 7 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Grok 4.7 | Saba | Leader |
|---|---|---|---|
| OTIS Mock AIME | 98.1% | Not measured | Only Grok 4.7 measured |
| FrontierMath, tiers 1 to 3 | 53.0% | Not measured | Only Grok 4.7 measured |
| FrontierMath, tier 4 | 17.1% | Not measured | Only Grok 4.7 measured |
| ProofBench | 26.0% | Not measured | Only Grok 4.7 measured |
| LMArena Text: math | 1414 | Not measured | Only Grok 4.7 measured |
| LMArena Text: mathematical work | 1435 | Not measured | Only Grok 4.7 measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Grok 4.7 | Saba | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | 84.4% | Not measured | Only Grok 4.7 measured |
| MedCode (Vals AI) | 49.5% | Not measured | Only Grok 4.7 measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 61.1% | Only Saba measured |
| SimpleQA Verified | 56.0% | Not measured | Only Grok 4.7 measured |
| LMArena Text: science | 1419 | Not measured | Only Grok 4.7 measured |
| LMArena Text: medicine and healthcare | 1395 | Not measured | Only Grok 4.7 measured |
| LMArena Text: legal and government | 1423 | Not measured | Only Grok 4.7 measured |
| LMArena Text: business and finance | 1389 | Not measured | Only Grok 4.7 measured |
| Neither model has a result on the other 9 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | Grok 4.7 | Saba | Leader |
|---|---|---|---|
| Design Arena: websites | 1254 | Not measured | Only Grok 4.7 measured |
| Design Arena: UI components | 1273 | Not measured | Only Grok 4.7 measured |
| Design Arena: game dev | 1312 | Not measured | Only Grok 4.7 measured |
| Design Arena: data viz | 1235 | Not measured | Only Grok 4.7 measured |
| Design Arena: 3D | 1270 | Not measured | Only Grok 4.7 measured |
| Design Arena: all code categories | 1271 | Not measured | Only Grok 4.7 measured |
| LiveBench design | 78.0% | Not measured | Only Grok 4.7 measured |
| Neither model has a result on the other 2 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index31 boards, none shared
| Benchmark | Grok 4.7 | Saba | Leader |
|---|---|---|---|
| Vals Index | 58.6% | Not measured | Only Grok 4.7 measured |
| LiveBench data analysis | 76.9% | Not measured | Only Grok 4.7 measured |
| Public Benefits Bench (Vals AI) | 65.6% | Not measured | Only Grok 4.7 measured |
| SAGE (Vals AI) | 40.8% | Not measured | Only Grok 4.7 measured |
| MedScribe (Vals AI) | 89.4% | Not measured | Only Grok 4.7 measured |
| Long context reasoning (AA-LCR) | 80.0% | Not measured | Only Grok 4.7 measured |
| DTBench | 96.0% | Not measured | Only Grok 4.7 measured |
| LMCA | 49.4% | Not measured | Only Grok 4.7 measured |
| Furniture assembly | 20.8% | Not measured | Only Grok 4.7 measured |
| LMArena Text | 1399 | Not measured | Only Grok 4.7 measured |
| LMArena Text: instruction following | 1406 | Not measured | Only Grok 4.7 measured |
| LMArena Text: creative writing | 1381 | Not measured | Only Grok 4.7 measured |
| LMArena Vision | 1231 | Not measured | Only Grok 4.7 measured |
| LMArena Text: English | 1411 | Not measured | Only Grok 4.7 measured |
| LMArena Text: non-English | 1386 | Not measured | Only Grok 4.7 measured |
| LMArena Text: Chinese | 1449 | Not measured | Only Grok 4.7 measured |
| LMArena Text: German | 1366 | Not measured | Only Grok 4.7 measured |
| LMArena Text: Japanese | 1359 | Not measured | Only Grok 4.7 measured |
| LMArena Text: Korean | 1383 | Not measured | Only Grok 4.7 measured |
| LMArena Text: French | 1431 | Not measured | Only Grok 4.7 measured |
| LMArena Text: Spanish | 1406 | Not measured | Only Grok 4.7 measured |
| LMArena Text: Russian | 1399 | Not measured | Only Grok 4.7 measured |
| LMArena Text: Polish | 1420 | Not measured | Only Grok 4.7 measured |
| LMArena Text: multi-turn | 1394 | Not measured | Only Grok 4.7 measured |
| LMArena Text: longer queries | 1416 | Not measured | Only Grok 4.7 measured |
| LMArena Text: writing and language | 1394 | Not measured | Only Grok 4.7 measured |
| LMArena Text: entertainment and media | 1376 | Not measured | Only Grok 4.7 measured |
| LMArena Vision: English | 1229 | Not measured | Only Grok 4.7 measured |
| LMArena Vision: Chinese | 1250 | Not measured | Only Grok 4.7 measured |
| LMArena Vision: reading text | 1241 | Not measured | Only Grok 4.7 measured |
| LMArena Vision: creative writing | 1217 | Not measured | Only Grok 4.7 measured |
| Neither model has a result on the other 15 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Grok 4.7 | Saba | Leader |
|---|---|---|---|
| Neither model has a result on 5 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
Grok 4.7$0.0050Fits in one request
Saba$0.0005Fits in one request
Saba costs less
Repository review
50K input + 3K output tokens
Grok 4.7$0.118Fits in one request
Saba$0.012Exceeds the context window
Saba costs less
Agent loop
200K input + 10K output tokens
Grok 4.7$0.460Fits in one request
Saba$0.046Exceeds the context window
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 | SpaceXAI Grok 4.7 | Mistral Saba |
|---|---|---|
| Maker | xAI | Mistral AI |
| Weights | No public weights listed | No public weights listed |
| Released | September 21, 2026 | February 17, 2025 |
| Context window | 500K | 33K |
| Input $/Mtok | $2.00 | $0.20 |
| Output $/Mtok | $6.00 | $0.60 |
| Coding index | 66.7 | Not benchmarked |
| Independent measurements behind it | 5 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Grok 4.7 better than Saba for coding?
Only Grok 4.7 has a coding score, 66.7 on the Vibe Coding Index; Saba has none, so the two cannot be ranked on coding. Saba has the edge where output tokens cost 10.0x less.
Which is cheaper, Grok 4.7 or Saba?
Grok 4.7 costs $2.00 per million input tokens and $6.00 per million output tokens; Saba costs $0.20 and $0.60. Cost per solved task is known for neither of them.
Which has the bigger context window, Grok 4.7 or Saba?
Grok 4.7, with 500K tokens against 33K.
How many benchmarks is the Grok 4.7 vs Saba comparison based on?
2 benchmarks have a result for both models as of October 21, 2026. Grok 4.7's coding index rests on 5 independent benchmarks and Saba's on 0. Where only one model has a result, the page says so instead of naming a winner.