Command R7B (12-2024) vs DeepSeek V4 Flash Vision Exp
Command R7B (12-2024) costs 8.8x less per output token than DeepSeek V4 Flash Vision Exp ($0.15 vs $1.32 per million). Updated October 21, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.15
- Coding
- No data
- Overall
- 56.4
- Output $/M
- $1.32
Command R7B (12-2024) or DeepSeek V4 Flash Vision Exp: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Command R7B (12-2024) for output tokens 8.8x cheaper ($0.15 vs $1.32 per million).
No benchmark has tested both yet. Command R7B (12-2024) has results on Berkeley Function Calling Leaderboard (BFCL); DeepSeek V4 Flash Vision Exp on LiveBench coding, AA Coding Index and SciCode. 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 DeepSeek V4 Flash Vision Exp has a AA Intelligence Index result, 34.8.
Directional only
Agentic work
AA Agentic Index
No call
Only DeepSeek V4 Flash Vision Exp has a AA Agentic Index result, 47.5.
Directional only
Long documents
Listed context window
DeepSeek V4 Flash Vision Exp
DeepSeek V4 Flash Vision Exp takes 1.05M tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Command R7B (12-2024)
Command R7B (12-2024) $0.0001, DeepSeek V4 Flash Vision Exp $0.0011 per turn.
List prices
At a glance
- Coding index
- Command R7B (12-2024) not benchmarked, DeepSeek V4 Flash Vision Exp 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 R7B (12-2024) $0.15 against DeepSeek V4 Flash Vision Exp $1.32 per million output tokens, 8.8x apart.
- Context window
- Command R7B (12-2024) takes 128K tokens, DeepSeek V4 Flash Vision Exp 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 R7B (12-2024) | DeepSeek V4 Flash Vision Exp | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 37.6% | Only DeepSeek V4 Flash Vision Exp measured |
| AA Coding Index | Not measured | 65.0 | Only DeepSeek V4 Flash Vision Exp measured |
| SciCode | Not measured | 49.7% | Only DeepSeek V4 Flash Vision Exp 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 | Command R7B (12-2024) | DeepSeek V4 Flash Vision Exp | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 34.8 | Only DeepSeek V4 Flash Vision Exp measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | Command R7B (12-2024) | DeepSeek V4 Flash Vision Exp | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 47.5 | Only DeepSeek V4 Flash Vision Exp measured |
| LiveBench research | Not measured | 69.2% | Only DeepSeek V4 Flash Vision Exp measured |
| LiveBench browser | Not measured | 64.0% | Only DeepSeek V4 Flash Vision Exp measured |
| LiveBench long agentic | Not measured | 39.0% | Only DeepSeek V4 Flash Vision Exp measured |
| Berkeley Function Calling Leaderboard (BFCL) | 32.1% | Not measured | Only Command R7B (12-2024) measured |
| Neither model has a result on the other 36 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | Command R7B (12-2024) | DeepSeek V4 Flash Vision Exp | Leader |
|---|---|---|---|
| LiveBench reasoning | Not measured | 85.4% | Only DeepSeek V4 Flash Vision Exp measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 91.3% | Only DeepSeek V4 Flash Vision Exp measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 34.5% | Only DeepSeek V4 Flash Vision Exp measured |
| Neither model has a result on the other 19 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Command R7B (12-2024) | DeepSeek V4 Flash Vision Exp | Leader |
|---|---|---|---|
| LiveBench design | Not measured | 70.7% | Only DeepSeek V4 Flash Vision Exp measured |
| Neither model has a result on the other 8 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Command R7B (12-2024) | DeepSeek V4 Flash Vision Exp | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 79.5% | Only DeepSeek V4 Flash Vision Exp measured |
| Long context reasoning (AA-LCR) | Not measured | 81.3% | Only DeepSeek V4 Flash Vision Exp measured |
| Neither model has a result on the other 44 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 R7B (12-2024) costs less
Repository review
50K input + 3K output tokens
Command R7B (12-2024) costs less
Agent loop
200K input + 10K output tokens
Command R7B (12-2024) 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 R7B (12-2024) | DeepSeek V4 Flash Vision Exp |
|---|---|---|
| Maker | Cohere | DeepSeek |
| Weights | No public weights listed | Open weights |
| Released | December 14, 2024 | August 21, 2026 |
| Context window | 128K | 1.05M |
| Input $/Mtok | $0.0375 | $0.44 |
| Output $/Mtok | $0.15 | $1.32 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Command R7B (12-2024) better than DeepSeek V4 Flash Vision Exp for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Command R7B (12-2024) for output tokens 8.8x cheaper ($0.15 vs $1.32 per million).
Which is cheaper, Command R7B (12-2024) or DeepSeek V4 Flash Vision Exp?
Command R7B (12-2024) costs $0.0375 per million input tokens and $0.15 per million output tokens; DeepSeek V4 Flash Vision Exp costs $0.44 and $1.32. Cost per solved task is known for neither of them.
Which has the bigger context window, Command R7B (12-2024) or DeepSeek V4 Flash Vision Exp?
DeepSeek V4 Flash Vision Exp, with 1.05M tokens against 128K.
Has any benchmark tested both Command R7B (12-2024) and DeepSeek V4 Flash Vision Exp?
No benchmark has tested both yet. Command R7B (12-2024) has results on Berkeley Function Calling Leaderboard (BFCL); DeepSeek V4 Flash Vision Exp on LiveBench coding, AA Coding Index and SciCode. Compare them on price and context instead. Data as of October 21, 2026.