Model comparison
DeepSeek V4.1 Flash vs Jamba Large
DeepSeek V4.1 Flash has enough public results to be ranked (#40); Jamba Large does not yet, so treat this comparison as directional.
Last verified . 0 shared benchmarks.
DeepSeekSummary
- The widest gap is in reasoning, where DeepSeek V4.1 Flash leads 46.2 to 17.4.
- DeepSeek V4.1 Flash is cheaper at $0.15 / $0.60 per million input/output tokens, against $2 / $8 for Jamba Large.
- DeepSeek V4.1 Flash accepts more context: 1M tokens versus 256K.
Side by side
| DeepSeek V4.1 Flash | Jamba Large | |
|---|---|---|
| Provider | DeepSeek | AI21 Labs |
| Noometry Index | 50.3 | 32.6 |
| Released | 2026-09-09 | 2025-07-01 |
| Weights | Open | Open |
| Context window | 1M | 256K |
| Max output | 393K | 4K |
| Input $ / M tokens | $0.15 | $2 |
| Output $ / M tokens | $0.60 | $8 |
| Results tracked | 25 | 2 |
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Category by category
Coding Not comparable
DeepSeek V4.1 Flash: 52.8 (#29), Jamba Large: —
| Benchmark | DeepSeek V4.1 Flash | Jamba Large |
|---|---|---|
| LMArena WebDev | 1620 | — |
| SciCode | 51.9% | — |
| LMArena Coding | 1511 | — |
| ALE-Bench | 1,092 | — |
Reasoning DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 46.2 (#39), Jamba Large: 17.4
| Benchmark | DeepSeek V4.1 Flash | Jamba Large |
|---|---|---|
| Kagi LLM Benchmark | — | 26.1% |
| NYT Connections (extended) | 89.6% | — |
| CritPt | 14.3% | — |
| LMArena Hard Prompts | 1485 | — |
| DTBench | 89.9% | — |
| LMCA | 47% | — |
| Surface Evolver Bench | 46.3% | — |
| Epoch Capabilities Index | 155.01 | — |
Math Not comparable
DeepSeek V4.1 Flash: 48.4 (#52), Jamba Large: —
| Benchmark | DeepSeek V4.1 Flash | Jamba Large |
|---|---|---|
| ProofBench | 54% | — |
| LMArena Math | 1493 | — |
Knowledge DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 41.6 (#97), Jamba Large: 37.0
| Benchmark | DeepSeek V4.1 Flash | Jamba Large |
|---|---|---|
| Vectara Hallucination Rate | — | 9.7% |
| LMArena Expert | 1505 | — |
Multilingual Not comparable
DeepSeek V4.1 Flash: 55.5 (#29), Jamba Large: —
| Benchmark | DeepSeek V4.1 Flash | Jamba Large |
|---|---|---|
| LMArena Non-English | 1452 | — |
| LMArena Chinese | 1506 | — |
| LMArena French | 1448 | — |
| LMArena Russian | 1473 | — |
| LMArena Spanish | 1499 | — |
Instruction Following Not comparable
DeepSeek V4.1 Flash: 77.6 (#24), Jamba Large: —
| Benchmark | DeepSeek V4.1 Flash | Jamba Large |
|---|---|---|
| LMArena Instruction Following | 1475 | — |
Long Context Not comparable
DeepSeek V4.1 Flash: 45.2 (#46), Jamba Large: —
| Benchmark | DeepSeek V4.1 Flash | Jamba Large |
|---|---|---|
| LMArena Longer Query | 1476 | — |
Writing & Preference Not comparable
DeepSeek V4.1 Flash: 65.8 (#43), Jamba Large: —
| Benchmark | DeepSeek V4.1 Flash | Jamba Large |
|---|---|---|
| LMArena Text | 1465 | — |
| LMArena Creative Writing | 1436 | — |
| EQ-Bench Creative Writing | 1540 | — |
| LMArena Multi-Turn | 1460 | — |
Frequently asked questions
Is DeepSeek V4.1 Flash better than Jamba Large?
DeepSeek V4.1 Flash has enough public results to be ranked (#40); Jamba Large does not yet, so treat this comparison as directional.
Which is cheaper, DeepSeek V4.1 Flash or Jamba Large?
DeepSeek V4.1 Flash is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; Jamba Large lists at $2 and $8.
Which has the bigger context window?
DeepSeek V4.1 Flash does, with 1M tokens against 256K.
How many benchmarks do DeepSeek V4.1 Flash and Jamba Large share?
0 benchmarks have published results for both models. DeepSeek V4.1 Flash has 25 scored results on Noometry and Jamba Large has 2.