Command R (08-2024) vs GPT-5.6 Sol Pro
Command R (08-2024) costs 33.3x less per output token than GPT-5.6 Sol Pro ($0.60 vs $20.00 per million). Updated October 21, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.60
- Coding
- No data
- Overall
- No data
- Output $/M
- $20.00
Command R (08-2024) or GPT-5.6 Sol Pro: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Command R (08-2024) for output tokens 33.3x cheaper ($0.60 vs $20.00 per million).
No benchmark has tested both yet. Command R (08-2024) has results on LMArena Text: coding, LMArena Text: software and IT and LMArena Text: hard prompts; GPT-5.6 Sol Pro on WeirdML, APEX-Agents and SimpleBench. 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
GPT-5.6 Sol Pro
GPT-5.6 Sol Pro takes 1.05M tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Command R (08-2024)
Command R (08-2024) $0.0004, GPT-5.6 Sol Pro $0.014 per turn.
List prices
At a glance
- Coding index
- Command R (08-2024) not benchmarked, GPT-5.6 Sol Pro 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
- Command R (08-2024) $0.60 against GPT-5.6 Sol Pro $20.00 per million output tokens, 33.3x apart.
- Context window
- Command R (08-2024) takes 128K tokens, GPT-5.6 Sol Pro 1.05M.
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 Index3 boards measured
| Benchmark | Command R (08-2024) | GPT-5.6 Sol Pro | Leader |
|---|---|---|---|
| WeirdML | Not measured | 89.4% | Only GPT-5.6 Sol Pro measured |
| LMArena Text: coding | 1187 | Not measured | Only Command R (08-2024) measured |
| LMArena Text: software and IT | 1197 | Not measured | Only Command R (08-2024) measured |
| Neither model has a result on the other 36 boards here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Command R (08-2024) | GPT-5.6 Sol Pro | Leader |
|---|---|---|---|
| APEX-Agents | Not measured | 51.4% | Only GPT-5.6 Sol Pro measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | Command R (08-2024) | GPT-5.6 Sol Pro | Leader |
|---|---|---|---|
| SimpleBench | Not measured | 71.7% | Only GPT-5.6 Sol Pro measured |
| Chess puzzles | Not measured | 68.0% | Only GPT-5.6 Sol Pro measured |
| LMArena Text: hard prompts | 1186 | Not measured | Only Command R (08-2024) measured |
| LMArena Text: expert | 1173 | Not measured | Only Command R (08-2024) measured |
| LMArena Text: hard prompts in English | 1194 | Not measured | Only Command R (08-2024) measured |
| Neither model has a result on the other 17 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | Command R (08-2024) | GPT-5.6 Sol Pro | Leader |
|---|---|---|---|
| FrontierMath, tier 4 | Not measured | 80.5% | Only GPT-5.6 Sol Pro measured |
| LMArena Text: math | 1188 | Not measured | Only Command R (08-2024) measured |
| LMArena Text: mathematical work | 1198 | Not measured | Only Command R (08-2024) measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | Command R (08-2024) | GPT-5.6 Sol Pro | Leader |
|---|---|---|---|
| LMArena Text: science | 1252 | Not measured | Only Command R (08-2024) measured |
| LMArena Text: medicine and healthcare | 1238 | Not measured | Only Command R (08-2024) measured |
| LMArena Text: legal and government | 1268 | Not measured | Only Command R (08-2024) measured |
| LMArena Text: business and finance | 1215 | Not measured | Only Command R (08-2024) measured |
| Neither model has a result on the other 14 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index16 boards measured
| Benchmark | Command R (08-2024) | GPT-5.6 Sol Pro | Leader |
|---|---|---|---|
| DTBench | Not measured | 96.0% | Only GPT-5.6 Sol Pro measured |
| LMCA | Not measured | 59.2% | Only GPT-5.6 Sol Pro measured |
| LMArena Text | 1229 | Not measured | Only Command R (08-2024) measured |
| LMArena Text: instruction following | 1197 | Not measured | Only Command R (08-2024) measured |
| LMArena Text: creative writing | 1234 | Not measured | Only Command R (08-2024) measured |
| LMArena Text: English | 1238 | Not measured | Only Command R (08-2024) measured |
| LMArena Text: non-English | 1216 | Not measured | Only Command R (08-2024) measured |
| LMArena Text: Chinese | 1227 | Not measured | Only Command R (08-2024) measured |
| LMArena Text: German | 1216 | Not measured | Only Command R (08-2024) measured |
| LMArena Text: Japanese | 1166 | Not measured | Only Command R (08-2024) measured |
| LMArena Text: Korean | 1162 | Not measured | Only Command R (08-2024) measured |
| LMArena Text: Russian | 1227 | Not measured | Only Command R (08-2024) measured |
| LMArena Text: multi-turn | 1213 | Not measured | Only Command R (08-2024) measured |
| LMArena Text: longer queries | 1230 | Not measured | Only Command R (08-2024) measured |
| LMArena Text: writing and language | 1241 | Not measured | Only Command R (08-2024) measured |
| LMArena Text: entertainment and media | 1223 | Not measured | Only Command R (08-2024) measured |
| Neither model has a result on the other 30 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
Command R (08-2024) costs less
Repository review
50K input + 3K output tokens
Command R (08-2024) costs less
Agent loop
200K input + 10K output tokens
Command R (08-2024) 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 | Cohere Command R (08-2024) | OpenAI GPT-5.6 Sol Pro |
|---|---|---|
| Maker | Cohere | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | August 30, 2024 | July 9, 2026 |
| Context window | 128K | 1.05M |
| Input $/Mtok | $0.15 | $4.00 |
| Output $/Mtok | $0.60 | $20.00 |
| 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 Command R (08-2024) better than GPT-5.6 Sol Pro for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Command R (08-2024) for output tokens 33.3x cheaper ($0.60 vs $20.00 per million).
Which is cheaper, Command R (08-2024) or GPT-5.6 Sol Pro?
Command R (08-2024) costs $0.15 per million input tokens and $0.60 per million output tokens; GPT-5.6 Sol Pro costs $4.00 and $20.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Command R (08-2024) or GPT-5.6 Sol Pro?
GPT-5.6 Sol Pro, with 1.05M tokens against 128K.
Has any benchmark tested both Command R (08-2024) and GPT-5.6 Sol Pro?
No benchmark has tested both yet. Command R (08-2024) has results on LMArena Text: coding, LMArena Text: software and IT and LMArena Text: hard prompts; GPT-5.6 Sol Pro on WeirdML, APEX-Agents and SimpleBench. Compare them on price and context instead. Data as of October 21, 2026.