Coding
Directional only- Grok Code Fast 1
- 32.5
- Estimated · #163/183
- MAI-Thinking-1
- 51.8
- Estimated · #60/183
- Basis
- BenchAlign lane · 1 vs 4 public rows
- Reading
- Directional only
Grok Code Fast 1 vs MAI-Thinking-1
Updated September 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
MAI-Thinking-1 has the higher public score, 52.27 versus 37.21, and the 90% score intervals do not overlap.
1 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
Share or export
Which one for your work
Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.
No workload recommendation clears the current evidence threshold.
Use the matched evidence, workload costs, and sourced specifications below instead of treating a point score as a universal answer.
Show secondary and unsupported calls
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Grok Code Fast 1 and MAI-Thinking-1 are scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Grok Code Fast 1 is not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limited
Long documents
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documented
Chat turn cost
1K fresh input + 500 output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: rate-fallback
Repository review cost
50K fresh input + 3K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
1 Shared
13 MAI-Thinking-1 only
- Shared results
- 1
- Grok Code Fast 1 only
- 0
- MAI-Thinking-1 only
- 13
- Like-for-like categories
- 0 / 8
3 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.
Category results, on a stated basis
Each row shows the public-lane category score for both models: the BenchAlign lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.
Knowledge
Directional only- Grok Code Fast 1
- 39.1
- Estimated · #144/181
- MAI-Thinking-1
- 53.3
- Estimated · #68/181
- Basis
- BenchAlign lane · 0 vs 4 public rows
- Reading
- Directional only
Instruction following
Directional only- Grok Code Fast 1
- 48.2
- #83/120
- MAI-Thinking-1
- 94.7
- #1/120
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Directional only
Agentic
Not comparable- Grok Code Fast 1
- Not ranked
- MAI-Thinking-1
- 51.7
- Estimated · #53/151
- Basis
- BenchAlign lane · 0 vs 1 public rows
- Reading
- Not comparable
Reasoning
Not comparable- Grok Code Fast 1
- 57.7
- Unranked · 2 rankable rows
- MAI-Thinking-1
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Grok Code Fast 1
- Not ranked
- MAI-Thinking-1
- 73.4
- Unranked · 3 rankable rows
- Basis
- Provisional lane · 0 vs 2 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Grok Code Fast 1
- Not ranked
- MAI-Thinking-1
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Grok Code Fast 1
- Not ranked
- MAI-Thinking-1
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Grok Code Fast 1 | MAI-Thinking-1 | Basis | Reading |
|---|---|---|---|---|
| Coding | 32.5Estimated · #163/183 | 51.8Estimated · #60/183 | Directional onlyBenchAlign lane · 1 vs 4 public rows | Directional only |
| Knowledge | 39.1Estimated · #144/181 | 53.3Estimated · #68/181 | Directional onlyBenchAlign lane · 0 vs 4 public rows | Directional only |
| Instruction following | 48.2#83/120 | 94.7#1/120 | Directional onlyProvisional lane · 0 vs 1 weighted rows | Directional only |
| Agentic | Not ranked | 51.7Estimated · #53/151 | Not comparableBenchAlign lane · 0 vs 1 public rows | Not comparable |
| Reasoning | 57.7Unranked · 2 rankable rows | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | Not ranked | 73.4Unranked · 3 rankable rows | Not comparableProvisional lane · 0 vs 2 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.
Shape of the matched evidence
Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.
Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.
SWE-bench Verified
Coding
Grok Code Fast 1: 70.8%MAI-Thinking-1: 73.5%Normalized gap 2.7Grok Code Fast 1 source MAI-Thinking-1 source
What each workload costs
Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.
Chat turn
1K fresh input + 500 output tokens
- Grok Code Fast 1
- $0.00095
- Fits in one request
- MAI-Thinking-1
- API rate not published
- Fits in one request
MAI-Thinking-1 has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- Grok Code Fast 1
- $0.0145
- Fits in one request
- MAI-Thinking-1
- API rate not published
- Fits in one request
MAI-Thinking-1 has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Grok Code Fast 1
- $0.059
- Fits in one request
- Cached input priced at the published list-input rate
- MAI-Thinking-1
- API rate not published
- Fits in one request
- Cached-input rate unavailable
Grok Code Fast 1 has no published cached-input rate, so cached tokens use its listed input rate. MAI-Thinking-1 has no comparable published API token rate.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationGrok Code Fast 1MAI-Thinking-1
Context window
Maximum documented context; output-token limits may be lower.
Grok Code Fast 1
256K
MAI-Thinking-1
256K
API model ID
Grok Code Fast 1
Not sourced
MAI-Thinking-1
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Grok Code Fast 1
Not published
MAI-Thinking-1
No comparable hosted API rate
Documented inputs
Grok Code Fast 1
Not sourced
MAI-Thinking-1
Not sourced
Documented outputs
Grok Code Fast 1
Not sourced
MAI-Thinking-1
Not sourced
Provider availability
Grok Code Fast 1
Not sourced
MAI-Thinking-1
Not sourced
Reasoning profile
Grok Code Fast 1
Non-Reasoning
MAI-Thinking-1
Reasoning
Weight access
Grok Code Fast 1
Proprietary
MAI-Thinking-1
Proprietary
License
Grok Code Fast 1
Proprietary
MAI-Thinking-1
Proprietary
Release date
Grok Code Fast 1
2025-08-28
MAI-Thinking-1
2026-06-02
If you already use one of these models
- Deployment change
- The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
- Quality signal
- MAI-Thinking-1 has the higher public score, 52.27 versus 37.21, and the 90% score intervals do not overlap.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- Both models list 256K.
Run the same representative tasks against both endpoints before changing production traffic.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence14 rows
Agentic
Terminal-Bench 2.0
Grok Code Fast 1—MAI-Thinking-146%SourceNot directly comparable
Coding
SWE-bench Verified
Grok Code Fast 170.8%SourceMAI-Thinking-173.5%SourceMAI-Thinking-1 leads this result
LiveCodeBench v6
Grok Code Fast 1—MAI-Thinking-187.7%SourceNot directly comparable
SWE-bench Pro
Grok Code Fast 1—MAI-Thinking-152.8%SourceNot directly comparable
Terminal-Bench 2.0
Grok Code Fast 1—MAI-Thinking-146.0%SourceNot directly comparable
Reasoning
Graphwalks BFS 128K
Grok Code Fast 1—MAI-Thinking-190%SourceNot directly comparable
Knowledge
Math
Instruction following
IFBench
Grok Code Fast 1—MAI-Thinking-185%SourceNot directly comparable
Frequently asked questions
Which is better, Grok Code Fast 1 or MAI-Thinking-1?
MAI-Thinking-1 has the higher public score, 52.27 versus 37.21, and the 90% score intervals do not overlap. That is the clearest overall quality signal in the current public data.
Which is better for coding, Grok Code Fast 1 or MAI-Thinking-1?
MAI-Thinking-1 scores higher for coding on the public lane, 51.8 to 32.5. Grok Code Fast 1 and MAI-Thinking-1 are scored on Estimated evidence for coding, so the reading is directional rather than like-for-like. BenchLM does not name a winner for coding from a directional reading; read the shared benchmark rows directly and test the models on the same task set.
Which is better for agentic tasks, Grok Code Fast 1 or MAI-Thinking-1?
Grok Code Fast 1 is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, Grok Code Fast 1 or MAI-Thinking-1?
Both models do not have comparable published API token rates, so this page does not name a universal price winner.
Which has the larger context window, Grok Code Fast 1 or MAI-Thinking-1?
Both models list the same context window, 256K.
Related comparisons
Last updated September 4, 2026
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