Chat turn cost
1K fresh input + 500 output tokens
Microsoft-Decision-1
Microsoft-Decision-1 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Updated October 20, 2026. We do not rank this pair: at least one has no public score. Public scores include evidence status and uncertainty.
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. Use the documented cost, context, and runtime rows instead. 0 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
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.
1K fresh input + 500 output tokens
Microsoft-Decision-1
Microsoft-Decision-1 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
50K fresh input + 3K output tokens
Microsoft-Decision-1
Microsoft-Decision-1 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Grok 3 Mini and Microsoft-Decision-1 are not ranked on the public lane for coding, so no winner is named for coding.
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Grok 3 Mini and Microsoft-Decision-1 are not ranked on the public lane for agentic, so no winner is named for agentic.
Prompts that approach the documented context limit
Not enough matched evidence
A complete context comparison is not sourced.
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Grok 3 Mini does not fit this workload in one request. Grok 3 Mini has no published cached-input rate, so cached tokens use its listed input rate. Microsoft-Decision-1 has no published cached-input rate, so cached tokens use its listed input rate.
Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.
The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.
Not comparable · BenchAlign v5.8
The coding row is not comparable on the public lane: at least one model is not measured or not ranked there.
Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.
A shared-evidence shape is not available.
BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.
Each row shows the public-lane category score for both models: the BenchAlign v5.8 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.
| Category | Grok 3 Mini | Microsoft-Decision-1 | Basis | Reading |
|---|---|---|---|---|
| Agentic | Not ranked | Not ranked | Not comparableBenchAlign v5.8 lane · 0 vs 0 public rows | Not comparable |
| Coding | Not ranked | Not ranked | Not comparableBenchAlign v5.8 lane · 1 vs 0 public rows | Not comparable |
| Reasoning | 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 |
| Knowledge | Not ranked | Not ranked | Not comparableBenchAlign v5.8 lane · 1 vs 0 public rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | 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 v5.8) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.
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.
1K fresh input + 500 output tokens
Microsoft-Decision-1 has the lower modeled cost
Costs use the listed standard API rates.
50K fresh input + 3K output tokens
Microsoft-Decision-1 has the lower modeled cost
Costs use the listed standard API rates.
200K cached + 20K fresh input + 10K output tokens
Grok 3 Mini does not fit this workload in one request. Grok 3 Mini has no published cached-input rate, so cached tokens use its listed input rate. Microsoft-Decision-1 has no published cached-input rate, so cached tokens use its listed input rate.
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
Maximum documented context; output-token limits may be lower.
Grok 3 Mini
128K
Microsoft-Decision-1
Not sourced
Grok 3 Mini
Not sourced
Microsoft-Decision-1
Microsoft-Decision-1
Microsoft-Decision-1 announcementA missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Grok 3 Mini
Not published
Microsoft-Decision-1
Not published
Microsoft-Decision-1 announcementGrok 3 Mini
Not sourced
Microsoft-Decision-1
Not sourced
Grok 3 Mini
Not sourced
Microsoft-Decision-1
Not sourced
Grok 3 Mini
Not sourced
Microsoft-Decision-1
Not sourced
Grok 3 Mini
Reasoning
Microsoft-Decision-1
Unspecified
Grok 3 Mini
Proprietary
Microsoft-Decision-1
Proprietary
Grok 3 Mini
Proprietary
Microsoft-Decision-1
Proprietary
Grok 3 Mini
2025-02-19
Microsoft-Decision-1
2026-10-12
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. The page therefore keeps the decision tied to the specific documented workload.
Grok 3 Mini and Microsoft-Decision-1 are not ranked on the public lane for coding, so no winner is named for coding.
Grok 3 Mini and Microsoft-Decision-1 are not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
For the stated presets, chat costs $0.00055 on Grok 3 Mini and $0.00004 on Microsoft-Decision-1; repository review costs $0.0165 and $0.0021; the cache-heavy agent loop costs $0.071 and $0.00924. Grok 3 Mini does not fit this workload in one request. Grok 3 Mini has no published cached-input rate, so cached tokens use its listed input rate. Microsoft-Decision-1 has no published cached-input rate, so cached tokens use its listed input rate.
A complete documented context-window comparison is not available.
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
One weekly email when material rank, price, or benchmark evidence changes make this matchup worth revisiting.
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Last updated October 20, 2026